machine learning engineer

ai engineer

data scientist

senior software engineer

data engineer

data engineering lead

LSEG (London Stock Exchange Group)

<div>Manager, Data Engineering Lead
SwapClear and Listed Rates, LCH Ltd, London
<div><h1 class="jobSectionHeader">LCH, SwapClear and Listed Rates</h1></div>
LCH Ltd is an international multi-asset class central counterparty clearing house (CCP), part of the London Stock Exchange Group. LCH Ltd serves a broad range of exchanges and over-the-counter trading platforms providing critical risk management services. It has a unique membership model and its customers span the globe and include major financial groups (including the majority of the major investment banks), broker-dealers and specialist commodity houses and a wide range of buy-side and real-money firms including major asset managers and large hedge funds.
This role provides an opportunity to work on one of the most critical finance technology functions in the world. The LCH CCP is systematically significant to the world&rsquo;s financial markets which requires technology that has to be very resilient and with strong controls. LSE Group also provides a chance to work with other technology teams across the Exchange, and the rest of the Post Trade Businesses
LCH SwapClear &amp; Listed Rates is the major clearing business for LCH and LSEG, one of the company flagships and the global leader in IRS Clearing. SwapClear is the largest global Rates platform in the world with the highest standards of resilience. The Platform clears ~9m new trades per annum and supports various daily post-trade processing features, such as margin optimisations. 90% of the cleared interest rate swaps globally pass through the platform, and we regularly clear in excess of $3.5 trillion notional per day with over 60 member bank groups and over 1000 clients serviced.<div><h1 class="jobSectionHeader">
Role Profile</h1></div>
The Reporting &amp; Data Analytics platform underpins regulatory reporting, risk visibility, member reporting and internal analytics across SwapClear and Listed Rates. Given the scale, criticality and regulatory scrutiny of this data, the platform is subject to exacting availability, accuracy, lineage and governance requirements.
LCH has embarked on a strategic transformation of its Reporting &amp; Data Analytics architecture, moving from legacy on-premise Oracle / Informatica stacks to a cloud native, Snowflake based data platform. This solution will enable robust, performant reporting, self-service analytics, and new data distribution patterns for our members and clients.
Joining as a Senior Engineer, you will be accountable for setting the platform&rsquo;s technical direction, delivering Reporting &amp; Data Analytics features, and ensuring the ongoing stability of the platform during and beyond the transformation.
You will be a technology leader with deep hands-on data engineering experience, strong technical judgement, and the seniority to engage confidently with Group Architecture, Group Data Governance, and senior business partners.
You will lead a team of engineers to deliver the reporting and data analytics transformation, with responsibility for technical standards and professional development. You will ensure the team designs and builds solutions in line with our Engineering Principles, taking a data-driven approach, innovating with purpose, and acting as an owner.
You will ensure the platform evolves beyond migration into a scalable, governed platform that supports our members and clients, and internal partners. 
<div><h1 class="jobSectionHeader">Key Responsibilities</h1></div><ul><li>
Technology owner of the end-to-end data solutions for reporting and data analytics across SwapClear and Listed Rates.</li><li>
Lead the safe migration from legacy Oracle / Informatica platform to the target cloud architecture. Take accountability for successful legacy decommissioning, not just building the new platform.</li><li>
Lead the design, implementation and multi-year phased delivery for SwapClear and Listed Rates.</li><li>
Define and drive evolution of the Strategic Cloud data platform, ensure it is fit for purpose for SwapClear and Listed Rates use cases.</li><li>
Ensure the E2E platform meets availability, performance, resilience and security expected of a &quot;systemically important&quot; clearing house.</li><li>
Assists Product Owners and Delivery Leads with delivery planning of business goals/outcomes.</li><li>
Act as a senior technical partner to Group Architecture Authority, Group Data Governance and Product and business partners.</li><li>
Partner with Quality engineering to ensure that all aspects of the software development lifecycle is delivered to high levels of quality and using modern testing standards, automation and cloud-native practices.</li><li>
Build and maintain strong relationships with internal and external partners, using influence and trust to drive alignment, resolve challenges, and promote shared quality goals. 
</li></ul><div><h1 class="jobSectionHeader">
Required Experience, Skills and Traits</h1></div><ul><li>
15+ years of hands-on software engineering experience, including at least 5+ years as a technical lead, with consistent track record of delivering high-quality solutions</li><li>
Shown leadership of enterprise scale Snowflake (or similar) data platform implementations.</li><li>
ELT data architectures, using dbt or similar</li><li>
Cloud data lake and data warehouse solutions</li><li>
Solid experience of data-centric solution using SQL, PL/SQL and Python</li><li>
Data warehouse modelling approaches</li><li>
Deep expertise in<ul><li>
Immutable, incremental and versioned data architectures</li><li>
Enterprise scale data modelling</li><li>
Data governance, lineage and control frameworks</li></ul></li><li>
Strong engineering background with the ability to engage deeply in design and implementation.</li><li>
Prior experience working with Informatica PowerCenter or similar solutions.</li><li>
Quality-first approach</li><li>
Seniority and credibility to influence group level architecture and governance bodies.</li><li>
Passionate about metrics driven approach and leading with data.</li><li>
Practical and relevant AI experience in data engineering / migrations use cases</li><li>
Detail oriented problem solver, comfortable &ldquo;diving-deep&rdquo;</li></ul>
Desired Experience, Skills and Traits<ul><li>
Experience operating in regulated, high availability environments.</li><li>
Degree in Computer Science, Software Engineering or equivalent.</li><li>
Knowledge and practical experience running technology both on prem and in cloud.</li><li>
Experience of large-scale real-time and batch process orchestration, optionally with third-party orchestration engines</li><li>
Good understanding of cyber security standards and practices and follows secure-by-design principle.</li><li>
Experience of working with agile frameworks like Scrum, Kanban.</li><li>
Background working in financial industry</li><li>
Experience of modern observability platforms e.g. DataDog</li></ul><div><h1 class="jobSectionHeader">
About the London Stock Exchange Group</h1></div>
LSEG&rsquo;s vision is to be the most trusted expert in global financial markets. This is achieved through leading the world in providing access to capital, helping customers optimise capital resources and promoting trusted and transparent environments and services for investment.
LSEG is a diversified international exchange Group that sits at the heart of the world's financial community. The Group operates through four key business divisions: Capital Markets (broad range of international equity, bond and derivatives markets); Post Trade (post trade and risk management services); Global Technology Services (high performance trading platforms and capital markets software); and Information Services (real-time and reference data products).
LSEG prides itself on operating a neutral, trusted, well-regulated and systemically important market infrastructure and does this within a fast paced, real-time and highly regulated environment. The Group is accountable to its shareholders, clients, regulators and the societies in which it operates and the Group Values and Behaviours underpin how the Group meets those accountabilities.
Career Stage:
Manager
London Stock Exchange Group (LSEG) Information:
Join us and be part of a team that values innovation, quality, and continuous improvement. If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.
LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.
Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.
Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.
We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone&rsquo;s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.
LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.
Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it&rsquo;s used for, and how it&rsquo;s obtained, your rights and how to contact us as a data subject.
If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.</div>

Data Engineering Lead

BlackRock

<div><div><div><div>Locations: London, United Kingdom; Edinburgh, United Kingdom
Additional Locations: ED3 - 20 Brandon Street, Edinburgh</div></div></div></div>
 <div><h2 class="jobSectionHeader">Job description</h2>
<div>About this role
The VP AI Data Engineering Lead operates at the intersection of strategic influence, team leadership, and delivery excellence &mdash; playing a defining role in how AI-powered data and knowledge products are conceived, designed, and executed across the organization.
He/She/They lead a multi-team organization of AI agent engineers and data scientists &mdash; setting technical and delivery direction, building the team&rsquo;s capability, and holding accountability for the production systems powering the commercialized knowledge products.
He/She/They function as the most senior bridge between Product Management leadership, business functional stakeholders, and AI engineering &mdash; bringing the technical depth and strategic breadth to influence product vision while holding firm accountability for engineering delivery outcomes across multiple squads.
He/She/They sets the organizational standard for how product intent gets translated into technical reality, establishing engineering frameworks, authoring principles, and driving the culture of quality, accuracy, and ownership across the broader Product Lead community.
He/She/They are deeply experienced in the nuances of AI engineering, from agent workflow design and Vision AI evaluation to production validation, output-quality governance, and customer adoption of knowledge products. Beyond the delivery mandate, they are a builder of people and of technical leaders of tomorrow &mdash; developing high-performing teams and creating the conditions for others to do their best work.
This is a role for a leader who thinks in systems, acts with purpose, and measures their success not just by what ships, but by the commercial credibility and lasting organizational capability left behind.
Roles &amp; Responsibilities
<ul><li>Lead a team of AI agent engineers and data scientists &mdash; setting technical direction, managing delivery, driving performance, developing individual capability across the team, and building the talent bench across the function.
</li><li>Own end-to-end solution design &amp; delivery for complex AI features across multiple AI engineering squads building multi-agent, GenAI, and Vision AI workflows &mdash; ensuring consistency, quality, and strategic alignment at scale.
</li><li>Drive backlog prioritization at the product-area level, balancing customer value, technical feasibility, AI accuracy expectations, model/vision constraints, and team capacity
</li><li>Run sprint planning, team stand-ups, and retrospectives; create the operating rhythm and working environment for engineers and data scientists to do their best work
</li><li>Proactively engage and act as the bridge between the Product Management, business stakeholders and AI engineering &mdash; influencing product vision &amp; feature prioritization (definition, scope, and sequencing) from deep understanding of technical possibility and commercial reality influence feature.
</li><li>Partner with Product Managers to shape feature roadmaps, bringing technical and AI-specific insight that meaningfully influences what gets built, when, and at what quality bar.
</li><li>Drive structured refinement sessions with the team, ensuring stories are technically complete and aligned on solution approach before development begins.
</li><li>Define and enforce quality standards for user story delivery &mdash; including extraction accuracy, edge-case coverage, agent behaviour expectations, and non-functional requirements
</li><li>Lead post-implementation validation efforts &mdash; coordinating UAT, output-quality reviews, production monitoring, and closing the loop with stakeholders on commercial outcomes
</li><li>Support product activation and customer adoption &mdash; translating delivery milestones into customer-facing readiness for data/knowledge product rollout
</li><li>Define and champion organization-wide standards for user story authoring, solution design, backlog management, and delivery quality for AI-powered knowledge products
</li><li>Lead complex, cross-functional AI initiatives from discovery through delivery &mdash; managing dependencies, risks, and stakeholder expectations across teams.
</li><li>Coach and mentor team members, conduct performance conversations, and contribute to hiring decisions for the AI engineering and data science team.
</li><li>Establish frameworks for post-implementation validation, output-quality governance, production monitoring, and customer success during product activation and adoption at scale
</li><li>Identify systemic delivery bottlenecks and drive process improvements that raise velocity and quality across the product organization
</li><li>Build and mentor a high-performing team of AI agent engineers, and data scientists &mdash; driving hiring, onboarding, performance management, and career development at scale
</li><li>Shape organizational design, team structure, and operating model for the AI data engineering function as the business scales
</li></ul>Required Skills &amp; Experience
Technical Skills
<ul><li>Minimum 6-8 years of experience in AI Engineering Delivery Lead, or AI Program Lead, or Engineering Manager roles, with at-least 2-3 years operating as AI Engineering Principal within a SaaS, AI, or data-product organization.
</li><li>Deep expertise and Proven experience in AI solution design and technical scoping for AI-driven features &mdash; ideally including GenAI, LLM-based capabilities, Vision AI, and multi-agent workflows.
</li><li>Strong command of scaled Agile delivery, cross-team dependency management, and delivery governance frameworks, backlog management, sprint planning, and Agile delivery tooling at scale (Jira, Confluence, Miro, or equivalent)
</li><li>Ability to engage meaningfully with AI engineers and data scientists on architecture decisions, agent orchestration, prompt design, Vision AI trade-offs, and model behaviour
</li><li>Fluency in the AI product development lifecycle &mdash; extraction accuracy, model evaluation, prompt engineering considerations, non-deterministic behaviour, and production monitoring
</li><li>Solid understanding of evaluation approaches for AI outputs &mdash; accuracy metrics, ground-truth validation, human-in-the-loop review, and output-quality benchmarking
</li><li>Familiarity with unstructured data extraction challenges across document, image, and multimodal inputs.
</li><li>Advanced grasp of product analytics, AI output-quality measurement, and outcome-based evaluation frameworks for data/knowledge products
</li><li>Deep understanding of responsible AI principles (accuracy governance, data provenance, and user trust as they relate to commercialized AI outputs) and their practical implications for feature design, accuracy governance, customer trust, and regulatory considerations
</li></ul>Non-Technical &amp; Interpersonal Skills
<ul><li>Executive-level communication skills &mdash; able to operate fluidly between engineering stand-ups and boardroom strategy conversations.
</li><li>Excellent communication and stakeholder management skills &mdash; able to drive alignment across product, commercial, engineering, and domain-expert audiences
</li><li>Strong strategic thinking &mdash; able to connect present engineering decisions &amp; strategy to long-term commercial positioning of AI knowledge/data products.
</li><li>Strong analytical and structured problem-solving approach &mdash; breaks down complex extraction and knowledge-structuring problems into clear, actionable paths forward
</li><li>Emotional intelligence and people-first leadership style &mdash; able to inspire, coach, and hold a diverse team of engineers and scientists to a high bar; earns trust quickly across diverse stakeholder groups including customers, commercial, and technical teams.
</li><li>Business acumen &mdash; understands the fundamentals of financials services industry and/or software/data product business, and how product output quality &amp; timeliness directly affects customer trust and revenue.
</li></ul>Leadership &amp; Ownership
<ul><li>Proven track record of building, leading, and developing teams of engineers, data scientists, or technical specialists in an AI or data product context at scale.
</li><li>Demonstrable experience influencing product vision and feature strategy at the leadership level &mdash; shaping what gets built, not just how.
</li><li>Experience establishing organization-wide standards, frameworks, and practices that persist beyond individual initiatives.
</li><li>Proven ability to set technical direction, manage delivery, and drive accountability across a cross-functional team.
</li><li>Track record of mentoring individuals, running performance conversations, and contributing to hiring and team-building.
</li><li>Courage to push back on feature scope or timelines when extraction accuracy, reliability, or commercial viability &mdash; or team sustainability &mdash; are at risk
</li><li>Proven track record of owning complex AI delivery outcomes end-to-end, including post-launch validation and adoption.
</li><li>Hands-on experience with hiring, team design, performance management, and succession planning for technical AI teams.
</li><li>Ability to hold the bar on quality and delivery while advocating for the team &mdash; protecting focus, escalating constraints, and making hard prioritization calls
</li><li>A builder-of-builders mindset &mdash; measures success by the capability and culture left behind, not just the features shipped.
</li></ul>What This Role Offers
<ul><li>Direct leadership of a high performing team of AI agent engineers and data scientists working on commercially impactful AI systems &amp; knowledge product portfolio &mdash; with meaningful autonomy and ownership.
</li><li>Direct influence over organizational direction &mdash; working closely with executive leadership on product vision, hiring, and operating model decisions.
</li><li>A meaningful seat at the table in shaping product &amp; engineering strategy, feature prioritization, and delivery practices for commercialized AI capabilities
</li><li>A platform to build and lead a world-class organization of AI engineers, data scientists, and Product Leads &mdash; creating lasting capability in commercialized AI.
</li><li>Direct exposure to emerging AI capabilities &mdash; multi-agent orchestration, GenAI, Vision AI &mdash; applied to real commercial problems at scale.
</li></ul><ul><li>A clear path toward head-of-Engineering function leadership roles, with investment in mentorship, external learning, and executive development.
</li></ul>Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work model
BlackRock&rsquo;s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person &ndash; aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock. 
 
Guidance on AI use for candidates 
 
At BlackRock, AI has long been part of how we work &ndash; enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we&rsquo;ve provided guidance( opens in new window) on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self. 
 
 
About BlackRock 
 
At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children&rsquo;s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress. 
 
This mission would not be possible without our smartest investment &ndash; the one we make in our employees. It&rsquo;s why we&rsquo;re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive. 
 
To learn more about BlackRock, please visit Careers.BlackRock.com( opens in new window). We also encourage you to get to know us on LinkedIn( opens in new window), Instagram( opens in new window), YouTube( opens in new window), X( opens in new window), and TikTok( opens in new window). 
 
BlackRock is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age, disability, race, religion, sex, sexual orientation and other protected characteristics at law.
</div><div>Job Requisition #
 
R264955</div></div>

AI Data Engineering Lead, Vice President

Selfridges

<div>Job Introduction
<div>
Here at Selfridges our customers are at the heart of everything we do, and we want to be known for delivering the best, most extraordinary experiences that keep our customers coming back. We are on a journey to build flexible, innovative technology platforms that create inspiring and effortless experiences across all our customer touchpoints.</div><div></div><div> 
Our Engineering team plays a central role in shaping these digital experiences, our e-commerce and digital platforms are central to creating innovative, customer-centric experiences. As we grow, we are looking for talented, curious individuals to join us, bring their unique perspectives, and help reimagine our digital platforms to new heights.</div><div></div><div> 
This is a hybrid role working from home and our offices in either London or Leicester.</div>
A bit about the role<div>
We&rsquo;re looking for a Tech Lead to help evolve Selfridges&rsquo; Enterprise Data Platform (EDP), the foundation that powers insights, personalisation, and data-driven decision-making across the business.</div><div></div><div> 
In this role, you&rsquo;ll be a leader in shaping the technical direction for our Snowflake-based data ecosystem while supporting the Architecture function. You&rsquo;ll work across Python, AWS, and Salesforce Data Cloud, helping to design, build, and optimise the pipelines and integrations that connect our digital, store, and enterprise systems.</div><div></div><div> 
Alongside your technical delivery, you&rsquo;ll indirectly manage a team of engineers, helping them grow their skills and ensuring best practices are embedded across the team. You&rsquo;ll collaborate closely with architects, analysts, and product teams to deliver secure, performant, and scalable data solutions that enable world-class experiences for our customers.</div><div></div> 
Key Responsibilities<ul><li>
Lead and contribute to defining the technical direction and standards of the Enterprise Data Platform in collaboration with architecture and engineering leads</li><li>
Support the Architecture function in designing scalable data models and integration patterns</li><li>
Lead by example through hands-on design and development ofdata pipelines in Python,SQL, and AWS services(Lambda, Glue, Step Functions, S3)</li><li>
Help evolve and maintain the Snowflake environment, focusing on optimisation, governance, and performance</li><li>
Collaborate on integrations between Snowflake, Salesforce, and enterprise systems, including future Salesforce Data Cloud enablement</li><li>
Partner with Power BIand analytics teams to ensure data reliability and accessibility for dashboards, insights, and reporting</li><li>
Work with DevOps and Platform Engineering to enhance CI/CD, observability, and automation practices for data workloads</li><li>
Drive a strong focus ondata quality,reusability, andperformanceacross all ingestion and transformation layers</li><li>
Collaborate across squads and domains to align data platform delivery with Selfridges&rsquo; wider digital and customer experience strategies</li></ul><div></div> 
A bit about you<ul><li>
Experienced data engineer or technical lead, ideally with previous line management or mentorship experience as you will in directly manage teams</li><li>
Strong hands-on experience with Snowflake and AWS data services(Lambda, Glue, Step Functions, S3, SNS/SQS)</li><li>
Proficient in Python and SQL, building reliable and maintainable ETL/ELT pipelines</li><li>
Solid understanding of data modelling(dimensional, star schema, or modern data mesh concepts)</li><li>
Experience integrating with Salesforce (CRM, APIs, or Data Cloud)</li><li>
Familiar with Power BI or similar BI tools for downstream analytics and reporting</li><li>
Knowledge of CI/CD,infrastructure as code(Terraform or CDK), and modern observability tooling</li><li>
Skilled communicator and collaborator, able to work effectively with architects, product managers, and cross-functional teams</li><li>
Passionate about engineering excellence,team development, and delivering data solutions that drive real business impact</li><li>
Enthusiastic about mentoring and supporting engineers&rsquo; growth, with a track record of building high-performing teams</li></ul><div></div> 
Desirable<ul><li>
Experience with dbt, Airflow, or Dagster</li><li>
Familiarity with event-driven architectures(EventBridge, Kafka, SNS/SQS)</li><li>
Exposure to data governance,security, and compliance frameworks</li><li>
Background inretail, loyalty, or customer data platforms</li><li>
Experience working with or implementingSalesforce Data Cloudintegrations</li><li>
Awareness ofAI/ML data readinesspractices, including feature engineering, dataset curation, and model-serving pipelines</li><li>
Familiarity withSnowflake Cortex,AWS Bedrock, or other cloud-native AI/ML services for data enrichment and automation</li><li>
Interest in emergingGenAI and LLMuse cases for personalisation, recommendation systems, and intelligent automation</li></ul></div>

Data Tech Lead

TPXimpact

<div><h3 class="jobSectionHeader">About The Role</h3>

Job level: 10 
 
We&rsquo;re looking for a Lead Data Engineer to join our Data Engineering and Analytics practice. 

In this role, you will: 
<div></div>
<ul>
<li>Lead the design, development, management and optimisation of data pipelines to ensure efficient data flows, recognising and sharing opportunities to reuse data flows where possible.
</li><li>Coordinate teams and set best practices and standards when it comes to data engineering principles.
</li><li>Champion data engineering across projects and clients. 
</li></ul><div></div><div>Responsibilities
<ul>
<li>Lead by example, holding responsibilities for team culture, and how projects deliver the most impact and value to our clients.
</li><li>Be accountable for the strategic direction, delivery and growth of our work.
</li><li>Lead teams, strands of work and outcomes, owning commercial responsibilities.
</li><li>Hold and manage uncertainty and ambiguity on behalf of clients and our teams.
</li><li>Ensure teams and projects are inclusive through how you lead and manage others.
</li><li>Effectively own and hold the story of our work, ensuring we measure progress against client goals and our DT missions.
</li><li>Work with our teams to influence and own how we deliver more value to clients, working with time and budget constraints.
</li><li>Strategically plan the overall project and apply methods and approaches.
</li><li>Demonstrably share work with wider audiences.
</li><li>Elevate ideas through how you write, speak and present. 
</li></ul><div><div>Dimensions</div> 
<div>
</div><div><ul><li>Headcount: Typically leads a multidisciplinary team or multiple workstreams (team size 5&ndash;15)
</li></ul><ul><li>Resource complexity: Provides leadership across multiple workstreams or technical domains within a project or programme. Responsible for delivery coordination, prioritisation, and quality, often overseeing more junior leads or specialists.
</li><li>Problem-solving responsibility: Solves highly complex problems, balancing technical, user, business, and operational needs. Applies expert judgement to make decisions, manage risks, and guide teams through ambiguity.
</li><li>Change management requirements: Leads or co-leads significant change initiatives. Responsible for managing stakeholder expectations, supporting adoption, and embedding sustainable ways of working.
</li><li>Internal/External interactions: Acts as a trusted partner to client and internal stakeholders at multiple levels. Leads workshops, presentations, and stakeholder engagement to ensure buy-in, alignment, and delivery clarity.
</li><li>Strategic timeframe working towards: Works across mid- to long-term delivery cycles (6&ndash;12 months), ensuring that near-term work supports broader programme and client objectives.
</li></ul></div></div></div><h3 class="jobSectionHeader">About You</h3>
Professional knowledge and experience

Essential
<ul>
<li>Proven experience in data engineering, data integration and data modelling
</li><li>Expertise with cloud platforms (e.g. AWS, Azure, GCP)
</li><li>Expertise with modern cloud data platforms (e.g. Microsoft Fabric, Databricks)
</li><li>Expertise with multiple data analytics tools (e.g. Power BI)
</li><li>Deep understanding of data warehousing concepts, ETL/ELT pipelines and dimensional modelling
</li><li>Proficiency in advanced programming languages (Python/PySpark, SQL)
</li><li>Experience in data pipeline orchestration (e.g. Airflow, Data Factory)
</li><li>Familiarity with DevOps and CI/CD practices (Git, Azure DevOps etc)
</li><li>Ability to communicate technical concepts to both technical and non-technical audiences
</li><li>Proven experience in delivery of complex projects in a fast paced environment with tight deadlines 
</li></ul> 
Desirable
<ul>
<li>Advanced knowledge of data governance, data standards and best practices.
</li><li>Experience in a consultancy environment, demonstrating flexibility and adaptability to client needs.
</li><li>Experience defining and enforcing data engineering standards, patterns, and reusable frameworks
</li><li>Professional certifications in relevant technologies (e.g. Microsoft Azure Data Engineer, AWS Data Analytics, Databricks Certified Professional Data Engineer) 
</li></ul><div></div><div>Skills

Data Development Process
<ul>
<li>Design, build and test data products that are complex or large scale</li>
<li>Build and lead teams to complete data integration services integration and reusable pipelines that meet performance, quality and scalability standards</li>
<li>Collaborate with architects to align solutions with enterprise data strategy and target architectures</li>
</ul>
Data Engineering and Manipulation
<ul>
<li>Work with data analysts, engineers and data science and AI specialists to design and deliver products into the organisation effectively.</li>
<li>Understand the reasons for cleansing and preparing data before including it in data products and can put reusable processes and checks in place.</li>
<li>Access and use a range of architectures (including cloud and on-premise) and data manipulation and transformation tools deployed within the organisation.</li>
<li>Optimise data pipelines and queries for performance and cost efficiency in distributed environments</li>
</ul>
Testing (Data)
<ul>
<li>Review requirements and specifications, and define system integration testing conditions for complex data products and support others to do the same</li>
<li>Identify and manage issues and risks associated with complex data products and support others to do the same</li>
<li>Analyse and report system test activities and results for complex data products and support others to do the same</li>
</ul>
Other Skills
<ul>
<li>Proficiency in developing and maintaining complex data models (conceptual, logical and physical).</li>
<li>Strong skills in data governance and metadata management.</li>
<li>Experience with data integration design and implementation.</li>
<li>Ability to write efficient, maintainable code for large scale data systems.</li>
<li>Experience with CI/CD pipelines, version control, and infrastructure-as-code (e.g. Git, Azure DevOps).</li>
<li>Strong stakeholder communication skills, with the ability to translate technical concepts into business terms.</li>
<li>Ability to mentor junior engineers, foster collaboration, and build a high-performing data engineering culture.</li>
</ul><div>Behaviours and PACT values
<ul><li>Purpose: Be values-driven, recognising that our client's needs are paramount. Approach client engagements with professionalism and creativity, balancing commercial and operational needs.</li>
<li>Accountability: Be accountable for delivering your part of a project on time and under budget and working well with other leaders. Lead by example, promoting a culture where quality and client experience are foremost.</li>
<li>Craft: Balance multiple priorities while leading high-performing teams. Navigate ambiguity and set the technical direction and approach to support positive outcomes.</li>
<li>Togetherness: Collaborate effectively with others across TPXimpact. Build strong relationships with colleagues and clients.</li></ul><div> 
</div>
 
</div></div><h3 class="jobSectionHeader">About Us</h3>
<div>People-Powered Transformation</div> 
<div></div>
<div>
We're a purpose driven organisation, supporting organisations to build a better future for people, places and the planet. Combining vast experience in the public, private and third sectors and expertise in human-centred design, data, experience and technology, we&rsquo;re creating sustainable solutions ready for an ever-evolving world. 


At the heart of TPXimpact, we&rsquo;re collaborative and empathetic. We&rsquo;re a team of passionate people who care deeply about the work we do and the impact we have in the world. We know that change happens through people, with people and for people. That&rsquo;s why we believe in people-powered transformation. 


Working in close collaboration with our clients, we seek to understand their unique challenges, questioning assumptions and building in their teams the capabilities and confidence to continue learning, iterating and adapting. 


Benefits Include:
<ul>
<li>30 days holiday + bank holidays</li>
<li>2 volunteer days for causes that you are passionate about</li>
<li>Maternity/paternity - 6 months Maternity Leave, 3 months Paternity Leave</li>
<li>Life assurance</li>
<li>Employer pension contribution of 5%</li>
<li>Health cash plan</li>
<li>Personal learning and development budget</li>
<li>Employee Assistance Programme</li>
<li>Green incentive programmes including Electric Vehicle Leasing and the Cycle to Work Scheme</li>
<li>Health assessments</li>
</ul>
</div><div>About TPXimpact - Digital Transformation 

We drive fundamental change in approaches to product and service development, delivery and technology. Our agile, multidisciplinary teams use technology, design and data to deliver better results, improving outcomes for individuals, organisations and communities. 
By working in the open, in partnership with our clients, we not only transform their systems and services but also build the capability of their teams, so work can continue without us in the longer term. Our focus is sustainable change, always delivered with positive impact. 


We&rsquo;re an inclusive employer, and we care about diversity in our teams. Let us know in your application if you have accessibility requirements during the interview.</div></div>

Lead Data Engineer

nSCALE

<div><h2 class="jobSectionHeader">About Nscale</h2>

Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale enables AI-focused companies to achieve superior results by reducing the complexity of AI development.

Our GPU cloud bolsters technical capabilities and directly supports strategic business outcomes, including cost management, rapid innovation, and environmental responsibility.

We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you'll build trust through openness and transparency, where everyone is inspired to do their best work. If you join our team, you'll be contributing to building the technology that powers the future.

<h2 class="jobSectionHeader">About the Role (Job Purpose)</h2>

We're looking for a Foundry Engineering Lead to serve as the technical authority for our Foundry implementation at Nscale&mdash;leading the design, development, and governance of the data platform that underpins our internal operations, workflows, and customer-facing capabilities.

This is a senior, high-impact role at the intersection of hands-on engineering and technical leadership. You'll set the architectural direction for Foundry, build and maintain the core data infrastructure, and work closely with Operations, Infrastructure, Platform Engineering, Product, and Commercial teams to deliver reliable, scalable data products.

As the most experienced Foundry engineer in the team, you'll mentor and guide other engineers and analysts, establish standards and best practices, and drive the technical roadmap as the platform scales.

This role is ideal for someone who combines deep, hands-on Foundry expertise with the confidence to lead technically&mdash;someone who can architect at scale, get into the details when it matters, and bring others along with them.

<h2 class="jobSectionHeader">What You'll be Doing (Responsibilities)</h2>
<ul>
<li>Lead the design and architecture of Nscale's Foundry implementation, ensuring scalability, security, and long-term data integrity.
</li>
<li>Define the technical strategy for Foundry development, aligning with business objectives and the programme-wide data roadmap.
</li>
<li>Act as the technical authority on Foundry across the organisation&mdash;setting standards, driving architectural decisions, and owning the evolution of the platform.
</li>
<li>Conduct code reviews and ensure adherence to best practices in data modelling, pipeline development, and integration.
</li>
<li>Mentor engineers and analysts working within the Foundry environment, raising technical capability and quality across the team.
</li>
<li>Design and build scalable, reliable data pipelines that ingest data from infrastructure, platform services, and business systems.
</li>
<li>Define data models, schemas, and ontology structures that support operational workflows and use cases across the business.
</li>
<li>Clean, transform, and structure data to create a digital twin of Nscale.
</li>
<li>Implement permissioning and manage access and security of the Foundry implementation.
</li>
<li>Create trusted datasets and metrics that power workflows, internal tools, and customer-facing insights.
</li>
<li>Enable self-service analytics by establishing clear data contracts, documentation, and semantic layers.
</li>
<li>Build use cases including, but not limited to:
<ul>
<li>Capacity planning
</li>
<li>Cost optimisation
</li>
<li>Reliability analysis
</li>
<li>Customer reporting
</li>
</ul></li><li>Collaborate with Product and Commercial teams to translate real-world business questions into robust data solutions.
</li>
<li>Implement data quality checks, monitoring, and alerting to ensure data correctness and availability.
</li>
<li>Codify data lineage, freshness, and consistency across systems.
</li>
<li>Establish and enforce governance standards around data versioning, access control, and compliance appropriate for a fast-scaling company.
</li>
<li>Oversee the integration of Foundry with existing systems and data sources, ensuring seamless data flows.
</li>
</ul><h2 class="jobSectionHeader">Profile and Required Skills</h2>
<ul>
<li>Deep, hands-on expertise in Palantir Foundry, including ontology modelling, pipeline development, data architecture, and large-scale platform design.
</li>
<li>Proven experience providing technical leadership&mdash;setting architectural direction, mentoring engineers, and defining standards in a data engineering context.
</li>
<li>Strong proficiency in Python, with experience applying data engineering frameworks (e.g. Spark, PySpark, Dask, pandas) to large, complex datasets.
</li>
<li>Familiarity with API-driven data integration, including REST, GraphQL, and Foundry Action APIs.
</li>
<li>Experience with Git-based development workflows, including code reviews, version control, and CI/CD pipelines.
</li>
<li>Excellent communication skills&mdash;able to explain complex technical concepts clearly to both technical and non-technical stakeholders.
</li>
<li>Comfortable operating in ambiguous, fast-moving environments where requirements evolve quickly.
</li>
<li>A bias toward ownership, pragmatism, and delivering useful solutions.
</li>
</ul><h3 class="jobSectionHeader">Nice to Have</h3>
<ul>
<li>Experience with cloud platforms (AWS, GCP, Azure) and infrastructure telemetry.
</li>
<li>Familiarity with distributed systems, monitoring data, or usage-based billing data.
</li>
<li>Experience supporting customer-facing data products or platforms.
</li>
</ul><h2 class="jobSectionHeader">What We Can Offer You</h2>

At Nscale, you'll find a collaborative, supportive, and innovative environment where your contributions spark real impact. We're building something extraordinary, and we want you at the core.
<ul>
<li>Highly competitive package (base + equity) with reviews every 12 months.
</li>
<li>Join the fastest-growing tech startup, your chance to push boundaries, collaborate with brilliant minds, and make your mark on cutting-edge AI. ✨
</li>
<li>Expect a dynamic progression plan tailored to your ambitions. Grow by trying new things, leading, challenging the status quo, and owning your impact, always with our full support.
</li>
<li>Human-First Flexibility: We treat you as humans first. Our flexible workplace trusts Nscalers to deliver, giving you the autonomy to shape your day around life's moments.
</li>
</ul><h1 class="jobSectionHeader">Equal Opportunities Statement</h1>

We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds.

If there's anything we can do to accommodate your specific situation, please let us know.

The responsibilities outlined in this job description are not exhaustive and are intended to provide a general overview of the position. The employee may be required to perform additional duties, tasks, and responsibilities as assigned by management, consistent with the skills and qualifications required for the role.<div>
For information on how Nscale handles candidate personal data, please see our Employee &amp; Candidate Privacy Notice: Here.</div></div>

Foundry Engineering Lead

Plentific

<div>
 
 
 About Us
 
 
 
 At Plentific, we&rsquo;re redefining property management in real time. Our mission, is to lead real estate through the transformative journey into &ldquo;The World of Now,&rdquo; enabling us to empower property professionals through our innovative, cloud-based platform.
 
 
 
 
 
 We harness cutting-edge technology and data-driven insights to streamline operations for landlords, letting agents, and property managers, enabling them to optimize maintenance, manage repairs, and make informed decisions instantly. Our platform is designed to create seamless, real-time workflows that transform traditional property management into a dynamic, digital experience.
 
 
 
 
 
 Backed by a world-class group of investors, including Noa, Highland Europe, Brookfields, Mubadala, RXR Digital Ventures, and Target Global, Plentific is at the forefront of the proptech revolution. Headquartered in London with a global outlook, we&rsquo;re continually expanding our reach and impact.
 
 
 
 
 
 We&rsquo;re looking for forward-thinking, passionate professionals who are ready to contribute to our mission and drive industry innovation. If you&rsquo;re excited about making an immediate impact and shaping the future of property management, explore career opportunities with us at Plentific.
 
 
 
 
 
 
 The Role
 
 
 
 We are looking for a
 
 Tech Lead - Data Engineering to serve as the primary architect and owner of our data platform. Reporting to the Head of Engineering, you will own the end-to-end technical direction of our data ecosystem and act as the most senior individual contributor in this domain.
 
 
 
 
 
 
 This role sits at the intersection of data engineering and system design. You will define how data is ingested, modelled, stored, transformed, and exposed across the company, with an emphasis on robust pipelines, clear data contracts, and reliable operation at scale.
 
 
 
 
 
 We are looking for someone who goes beyond building pipelines and focuses on designing durable, well-architected data systems. The large volumes of transactional data we generate form the foundation for machine learning and other AI-driven solutions that we are actively building and evolving. Your focus will be on designing and evolving data systems that are reliable, maintainable, and fit for long-term use, applying strong software engineering principles to how data is structured, integrated, and operated at scale.
 
 
 
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 
 Own the Data Platform:
 
 Take end-to-end ownership of the data platform, including ingestion, storage, transformation, and exposure layers. This includes setting technical direction and being accountable for system reliability, performance, and cost.
 </li>
 <li>
 
 System Architecture:
 
 Lead the design of distributed data systems, ensuring clean integration between backend services, external APIs, event streams, and data storage layers.
 </li>
 <li>
 
 ML-powered Product Enablement:
 
 Work closely with product and engineering teams to design and lead data foundations for machine-learning-powered product features, ensuring data quality, traceability, and production readiness.
 </li>
 <li>
 
 Data Modelling &amp; Strategy:
 
 Act as the lead architect for data models and contracts. Design schemas for both structured and unstructured data, balancing flexibility, performance, and long-term maintainability.
 </li>
 <li>
 
 Engineering Standards &amp; Artefacts:
 
 Set and uphold engineering standards across the data domain. Produce and maintain architecture diagrams, design documents, and Architecture Decision Records (ADRs). Champion best practices including version control, CI/CD, modular design, backwards compatibility, and automated testing.
 </li>
 <li>
 
 Pipeline &amp; ETL/ELT Design:
 
 Architect and implement high-scale, fault-tolerant data pipelines. Make deliberate trade-offs around latency, freshness, cost, and complexity, selecting fit-for-purpose tools rather than defaulting to trends.
 </li>
 <li>
 
 Hands-on Delivery:
 
 Spend a significant portion of your time building and maintaining core pipelines, schemas, and services in production. This is a hands-on role with direct responsibility for critical systems.
 </li>
 <li>
 
 Technical Leadership:
 
 Define the technical roadmap for data, perform deep code reviews, and mentor engineers on system design, SQL, and Python.
 </li>
 <li>
 
 Workflow Automation:
 
 Design and implement automated workflows (using tools such as n8n or custom Python services) to bridge operational gaps and reduce manual processes.
 </li>
 <li>
 
 Governance &amp; Security:
 
 Design enterprise-grade governance frameworks covering access control, data lineage, observability, and data integrity.
 </li>
 <li>
 
 Production Ownership:
 
 Be accountable for production incidents, data quality issues, and cost regressions within the data platform.
 </li>
 <li>
 
 
 ML-powered Product Enablement:
 
 
 
 Work closely with product and engineering teams to design and lead data foundations for machine-learning-powered product features, ensuring data quality, traceability, and production readiness.
 
 </li>
 </ul>
 
 
 
 
 
 Experience and Qualifications
 
 
 <ul>
 <li>
 
 
 Architectural Mindset:
 
 
 
 Proven experience as a Tech Lead, Principal Engineer, or System Architect designing and owning complex, distributed systems.
 
 </li>
 <li>
 
 
 Strong Software Engineering Foundations:
 
 
 
 A software-engineer-first mindset with deep experience in Python and production-grade engineering practices. Experience with libraries such as Pandas or Polars is expected, but architectural thinking matters more than specific tools.
 
 </li>
 <li>
 
 
 Machine Learning Exposure:
 
 
 
 Hands-on experience working with machine learning systems and tooling (e.g. Hugging Face, feature stores, model inference pipelines, or similar), with an emphasis on enabling ML in production rather than research experimentation.
 
 </li>
 <li>
 
 
 Database &amp; Storage Expertise:
 
 
 
 Advanced SQL skills and hands-on experience with modern cloud data warehouses (e.g. Snowflake or equivalent), alongside solutions for unstructured or semi-structured data.
 
 </li>
 <li>
 
 
 ETL/ELT &amp; Orchestration:
 
 
 
 Experience designing and operating modern data pipelines using tools such as dbt, Airflow, or equivalent orchestration and transformation frameworks.
 
 </li>
 <li>
 
 
 Engineering Rigor:
 
 
 
 Deep experience with Git-based workflows, CI/CD pipelines, automated testing, and maintaining long-lived systems in production.
 
 </li>
 <li>
 
 
 Engineering Judgement:
 
 
 
 Demonstrated ability to make and defend trade-offs&mdash;when to model data, when not to ingest data, and how to balance correctness, performance, and cost.
 
 </li>
 <li>
 
 
 Analytical Depth:
 
 
 
 Ability to interrogate and analyse data directly to validate system behaviour and ensure high levels of data quality.
 
 </li>
 </ul>
 
 
 
 
 
 Desirable
 
 
 <ul>
 <li>
 
 Experience with
 
 
 
 Analytics-as-Code
 
 
 
 platforms such as Looker/LookML.
 
 </li>
 <li>
 
 Experience building internal platforms that enable, rather than directly deliver, BI and reporting.
 
 </li>
 <li>
 
 Experience with automation platforms such as
 
 
 
 n8n
 
 
 
 for connecting operational systems.
 
 </li>
 <li>
 
 Experience designing systems for multimodal data (text, images, video, documents).
 
 </li>
 </ul>
 
 
 
 
 
 Benefits
 
 
 
 As you can see, we are quickly progressing with our ambitious plans and are eager to grow our team of doers to achieve our vision of managing over 2 million properties through our platform across various countries. You can help us shape the future of property management across the globe. Here&rsquo;s what we offer:
 
 <ul>
 <li>
 A competitive compensation package
 </li>
 <li>
 25 days annual holiday + 1 additional day for every year served up to 5 years.
 </li>
 <li>
 Flexible working environment including the option to work abroad
 </li>
 <li>
 Private health care for you and immediate family members with discounted gym membership, optical, dental and private GP
 </li>
 <li>
 Enhanced parental leave
 </li>
 <li>
 Life insurance (4x salary)
 </li>
 <li>
 Employee assistance program
 </li>
 <li>
 Company volunteering day and charity salary sacrifice scheme
 </li>
 <li>
 Learning management system powered by Udemy
 </li>
 <li>
 Referral bonus and charity donation if someone you introduce joins the company
 </li>
 <li>
 Season ticket loan, Cycle to work, Electric vehicle and Techscheme programs
 </li>
 <li>
 Pension scheme
 </li>
 <li>
 Work abroad scheme
 </li>
 <li>
 Company-sponsored lunches, dinners and social gatherings
 </li>
 <li>
 Fully stocked kitchen with drinks, snacks, fruit, breakfast cereal etc.
 </li>
 </ul>
 
 
 
</div>

Senior Data Engineer

JPMorganChase

<div>JOB DESCRIPTION 
 
 
Join us to shape the future of financial analytics and technology. You will lead impactful projects that drive advanced data engineering and AI solutions across global teams. We offer opportunities for career growth, collaboration, and technical excellence. Your expertise will help us deliver mission-critical systems and foster a culture of innovation. Be part of a team where your ideas and leadership make a difference. 
As a Lead Data Engineering &amp; AI Technical Initiatives in the Global Analytics team, you will guide technical direction and drive innovation in real-time data processing. You will collaborate with research and trading teams to deliver advanced analytics capabilities and support global business needs. Your role will focus on building robust tools, mentoring team members, and influencing product design. You will help shape our technical standards and foster a diverse, inclusive, and collaborative environment.
Job Responsibilities:<ul><li>
Lead technical initiatives across global analytics teams, providing guidance and direction in a high-velocity environment.</li><li>
Design, build, and optimize real-time data processing pipelines and applications to ensure reliability and performance.</li><li>
Leverage AI technologies to enhance data engineering workflows and automate SDLC processes.</li><li>
Collaborate with research and trading teams to onboard new datasets efficiently and consistently.</li><li>
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.</li><li>
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.</li><li>
Build and support robust tools and frameworks for quantitative research and production trading.</li><li>
Mentor and develop team members, manage book of work, and drive continuous improvement in SDLC, testing, and coding standards.</li><li>
Influence product design, application functionality, and technical operations to meet evolving business demands.</li><li>
Serve as a subject matter expert in Python, KDB/Q, data engineering, and AI.</li><li>
Champion diversity, inclusion, and collaboration within global teams.</li></ul>
Required Qualifications, Capabilities, and Skills:<ul><li>
Applied experience in software engineering, preferably in large-scale, fast-paced financial environments.</li><li>
Hands-on experience delivering system design, application development, testing, and operational stability for analytics-driven teams.</li><li>
Expertise in Python, KDB, or C++ for real-time data processing, application development, or data engineering.</li><li>
Working knowledge of AI technologies to support data engineering, analytics, or SDLC automation.</li><li>
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.</li><li>
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices</li><li>
Proficiency in automation and continuous delivery methods; advanced understanding of agile methodologies.</li><li>
Experience leading and mentoring teams in a global, collaborative environment.</li><li>
Ability to tackle complex design and functionality problems independently and drive solutions across distributed teams.</li><li>
Academic background in Computer Science, Computer Engineering, Mathematics, or a related technical field.</li></ul>
Preferred Qualifications, Capabilities, and Skills:<ul><li>
Experience with market data venue and vendor data platforms.</li><li>
AWS experience; practical cloud native/cloud experience is a plus.</li><li>
Experience with Terraform and Kubernetes for managing production environments in public cloud.</li><li>
Knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading
</li></ul>ABOUT US
 
 
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. 
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. 
</div></div> 
 
ABOUT THE TEAM
 
 
J.P. Morgan's Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

Lead Software Engineer - Python and kdb+ / AI data integration, Alt Data & Data Ingestion

Explore 515+ Data engineering lead in London this July. Find roles across top companies and apply now to boost your career.