data engineer

ai engineer

data scientist

machine learning engineer

senior data scientist

lead data engineer

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

SR2 | Socially Responsible Recruitment | Certified B Corporation™

<div>
 
 
 Lead Data Engineer &mdash; London, Full-time
 
 
 
 A fast-growing AI company is looking for its first senior data hire to own the entire data architecture. You'll build the pipelines, infrastructure, and ML data systems that power a platform already live with thousands of users &mdash; and help define how the data team grows from here.
 
 
 
 
 
 
 
 
 
 What you'll do
 
 
 <ul>
 <li>
 Architect and build scalable data pipelines for AI and product workloads
 </li>
 <li>
 Build and optimise vector search, retrieval, and ML data systems
 </li>
 <li>
 Own data reliability, quality, and observability across the platforms
 </li>
 <li>
 Work directly with founders and engineering, and help hire the future data team
 </li>
 </ul>
 
 
 
 
 
 What we're looking for
 
 
 <ul>
 <li>
 7+ years in data or backend engineering
 </li>
 <li>
 Strong Python skills
 </li>
 <li>
 Experience with relational databases (PostgreSQL preferred) and NoSQL
 </li>
 <li>
 Hands-on with vector databases (Qdrant, Milvus, pgvector or similar
 </li>
 <li>
 Familiarity with Spark, Airflow, or Kafka
 </li>
 <li>
 Experience with AI or ML platforms is a plus
 </li>
 <li>
 High-ownership mindset &mdash; you enjoy building from scratch
 </li>
 </ul>
 
 
 
 
 
 
 
 
 The opportunity
 
 
 
 Join early and own everything. This is a rare chance to define the data backbone of a category-defining AI company, working directly with the founders and core engineering team. We offer a competitive salary and meaningful equity
 
 
 
 
 
 
 
 
 If you're excited to build the data infrastructure powering a fast-scaling AI platform, we'd love to hear from you.
 
</div>

JPMorganChase

<div>JOB DESCRIPTION 
 
 
Embrace this pivotal role as an essential member of a high performing team dedicated to reaching new heights in data engineering. Your contributions will be instrumental in shaping the future of one of the world's largest and most influential companies.
As a Senior Lead Data Engineer at JPMorganChase within the Behavioral Insights Team, you will turn operational signals and platform data into actionable insights that improve reliability, risk/control health, and delivery efficiency. You will own the reliability and performance of reporting and analytics pipelines, define and govern SLIs/SLOs and error budgets, and automate data products (dashboards, scheduled reporting, and near-real-time views) that serve engineering, risk, and business stakeholders. You will also manage and mentor team members and uphold rigorous data management practices and controls.
Job Responsibilities<ul><li>
Change and release health - Track deployment frequency, change failure rate, lead time, and rollbacks; correlate changes to incidents/SLO impact; influence safer release practices.</li><li>
Capacity, performance, and scalability - Produce capacity forecasts, headroom and hotspot reporting; partner with engineering to validate scaling policies and performance budgets.</li><li>
FinOps and cost observability - Report spend by service/team/env; track unit economics (e.g., cost per transaction), rightsizing opportunities, commitment utilization, and tag compliance; highlight reliability&ndash;cost tradeoffs.</li><li>
Risk and controls compliance - Evidence guardrail adherence and control health (backup/restore posture, DR testing, patch/vulnerability closure, config drift); ensure metrics lineage and audit readiness.</li><li>
Uses enterprise-authorized AI capabilities within the work environment to accelerate data platform and design analysis and technical documentation, validating outputs and handling data according to sensitivity and security requirements.</li><li>
Data risk and controls - Monitor adherence to risk and control guidelines for data access and use.</li><li>
Data quality, reliability, and lineage - Define data contracts for telemetry sources; implement validation, anomaly detection, and reconciliation; document definitions (e.g., formulas, thresholds) and end-to-end data lineage from raw signals to KPIs and insights.</li><li>
Automation and self‑service - Deliver automated pipelines for scheduled reporting and near‑real‑time dashboards; enable RBAC‑controlled self‑service for teams and leadership.</li><li>
Stakeholder cadences and communication - Lead weekly reliability reviews and monthly leadership reviews; maintain action logs to closure; escalate risks early with data‑driven recommendations.</li><li>
People leadership - oversee workflow, prioritization, and delivery for junior data engineers and visualization researchers; mentor and support upskilling and career development.</li><li>
Applies reuse-first, AI-assisted practices within delivery and operational routines (e.g., validation automation and access control review support), ensuring traceability/auditability and alignment to resiliency and security expectations.</li></ul>
Required qualifications, capabilities, and skills<ul><li>
Formal training or certification on data engineering concepts and advanced applied experience in data analytics/BI/ operations analytics.</li><li>
Strong SQL skills (CTEs, window functions, performance-aware querying).</li><li>
Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.</li><li>
Ability to review and validate AI-assisted outputs (e.g., model and design summaries or validation recommendations) before use, escalating when uncertain and following data handling requirements.</li><li>
Hands-on experience building dashboards in Tableau/Power BI/Looker (or similar).</li><li>
Experience working with ITSM tools (e.g., ServiceNow or similar) and understanding incident/change/problem concepts.</li><li>
Strong data storytelling skills; ability to translate operational findings into practical improvements.</li></ul>
Preferred qualifications<ul><li>
Experience working with AWS and core concepts (accounts, regions, IAM, networking, compute/storage, tagging).</li><li>
Python for analytics/automation (e.g., pandas) and building repeatable pipelines.</li><li>
Experience with cloud data platforms (e.g., Snowflake/Redshift/BigQuery) and ELT tooling (e.g., dbt).</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>

Sr. Lead Data Engineer

Liberis

<div>Some key info for you about Liberis:

 We were founded in 2007

 We have provided over $3bn of funding to small businesses so far

 We have been named in CNBC &amp; Statista Top 150 UK Fintechs for 2025

 We're a global team, with a dynamic presence in 6 key locations around the world

 We're a thriving community of over 290 innovative minds

 We're a vibrant melting pot, celebrating over 27 nationalities in our team

 Our team brings experience from over 740 previous companies, from startups to global giants

 We have just been named as one of FinTech's Finest 50 by Welcome to the Jungle

 We're proud to be an accredited Real Living Wage employer, ensuring everyone is paid fairly for the great work they do! 


Our Product &amp; Engineering Team:

Liberis is building the embedded finance platform that lets partners around the world offer innovative funding products to their small business customers. We're a growth-stage fintech with teams in London, Nottingham, Atlanta, Stockholm, Munich and Mumbai, and we're building a global Product, Data &amp; Engineering team that thrives on autonomy, ownership, and is focused on impact! Our teams solve real-world problems for small businesses, shaping products that unlock opportunity at scale.

Engineering is going through an AI-first transformation, rethinking how teams are structured and how they ship. It's changing what a small team can do! We empower our teams to make decisions, move fast, and take full responsibility for the solutions they deliver. You'll join a team where curiosity is encouraged and collaboration across Product, Data, Delivery and Engineering is the norm. 


About our Data &amp; Insights Team:

We exist to build the data platforms and analytics that enable every decision at Liberis to be data-informed&mdash;and increasingly, to power AI and ML capabilities across the company!

We're building composable, reliable data platforms that scale&mdash;from ingesting partner transaction data and event streams, to powering analytics dashboards, to feeding ML models with real-time features. We're also supporting the AI/ML platform team with reliable, low-latency feature pipelines and model serving infrastructure.

We're collaborative, pragmatic, and we value moving fast by fixing the right problems&mdash;not over-engineering, but building to last! 


The team is made up of three functions:

Data Platform Engineering: Building and scaling ELT pipelines, managing data infrastructure on GCP, and creating the foundation for analytics and ML feature stores. You'll be part of a small, high-performing team of platform engineers focused on reliability, scale, and developer velocity.

Analytics Engineering: Transform raw data into trusted models using DBT and SQL, powering self-serve analytics and business intelligence for stakeholders across the company.

Data &amp; Business Intelligence: Build dashboards, partner-facing reports, and insights that drive business decisions and revenue outcomes. 


What you'll get to do in the role:
<ul>
<li>Design, build, and maintain resilient data pipelines that ingest data from Azure SQL, SaaS platforms, and event streams into BigQuery.</li>
<li>Write Python code using DLT to define declarative, testable, version-controlled pipelines - no low-code tools, real engineering.</li>
<li>Build and operate ML feature pipelines - low-latency, real-time data streams that feed ML models with accurate, fresh features.</li>
<li>Own the operational health of systems you build - monitoring, alerting, error handling, and incident response. When the data pipeline goes down, merchant credit decisions and ML model predictions suffer.</li>
<li>Collaborate with analytics engineers to understand data needs, validate schema design, and establish data quality standards that both analytics and ML rely on.</li>
<li>Partner with the AI/ML platform team to design feature stores, streaming feature infrastructure, and model serving pipelines that power Liberis' decisioning engine.</li>
<li>Identify and execute optimisation work - improving performance, reliability, and developer velocity without rearchitecting stable systems.</li>
<li>Mentor junior engineers, helping them grow as engineers and supporting their career development.</li>
<li>Participate in technical decisions about platform direction - infrastructure choices, tooling, architecture trade-offs.</li>
<li>Work cross-functionally with product teams, analytics engineers, BI specialists, and the ML platform team to shape data requirements and platform capabilities.</li></ul> 


What we think you'll need:
<ul>
<li>Proven experience within data engineering roles -building and operating data pipelines at scale</li>
<li>Hands-on experience building Modern Data Stack architectures - you understand the layers: ingestion, warehouse, transformation, orchestration, reverse ETL. You've worked with tools like DLT/Fivetran/Airbyte (ingestion), BigQuery/Snowflake/Redshift (warehouse), DBT (transformation), Airflow/similar (orchestration).</li>
<li>Strong Python programming - you write clean, testable, maintainable code with solid error handling and logging.</li>
<li>Fluent SQL - you can write complex queries, understand execution plans, and optimize for performance and cost.</li>
<li>Experience with cloud data platforms - you've built data warehouses in BigQuery, Redshift, Snowflake, or similar; you understand distributed processing, partitioning, cost optimization, and data governance.</li>
<li>Experience with infrastructure-as-code tools (Terraform, CloudFormation, Pulumi) or equivalent - you version control infrastructure and deploy it via CI/CD pipelines.</li>
<li>Experience working in fast-moving environments where requirements evolve and you adapt quickly without losing sight of reliability.</li>
<li>Understanding of DevOps principles - you think in terms of observability, resilience, incident response, and operational excellence. You can set up monitoring and alerting that actually matters.</li></ul> 


Bonus points if you have:
<ul>
<li>Experience with DLT or similar declarative ELT frameworks; experience with Google Cloud Platform ecosystem (BigQuery, Cloud Run, Pub/Sub, Dataflow); experience with Kafka, Pub/Sub, or event streaming platforms; experience scaling data systems from 0 to 100M+ events/day; experience implementing data quality frameworks (Great Expectations, dbt tests, custom monitoring); background in fintech or high-stakes data reliability environments where data quality directly impacts revenue.</li>
<li>Experience working with distributed, asynchronous teams across timezones; experience in India tech ecosystem or building in resource-constrained environments; experience migrating from legacy data infrastructure (Azure ADF, traditional ETL) to modern cloud-native stacks.</li></ul> 

<div>
Career development is really important to us here at Liberis, with progression opportunities for both individual contributors and people managers. You can have a look through our Engineering Career Framework via this link</div>
<div> 
Our hybrid approach 
Working together in person helps us move faster, collaborate better, and build a great Liberis culture. Our hybrid working policy requires team members to be in the office at least 3 days a week. At Liberis, we embrace flexibility as a core part of our culture, while also valuing the importance of the time our teams spend together in the office. 
 
#LI-FC1</div></div>

<div>JOB DESCRIPTION 
 
 
At JP Morgan Chase, we understand that customers seek exceptional value and a seamless experience from a trusted financial institution. That's why we launched Chase UK to transform digital banking with intuitive and enjoyable customer journeys. With a strong foundation of trust established by millions of customers in the US, we have been rapidly expanding our presence in the UK and soon across Europe. We have been building the bank of the future from the ground up, offering you the chance to join us and make a significant impact.
As a Lead Data Engineer at JPMorgan Chase within the International Consumer Bank, you will play a crucial role in this initiative, dedicated to delivering an outstanding banking experience to our customers. You will work in a collaborative environment as part of a diverse, inclusive, and geographically distributed team. We are seeking individuals with a curious mindset and a keen interest in new technology.
Our engineers are naturally solution-oriented and possess an interest in the financial sector and focus
 
on addressing our customer needs. We work in teams focused on specific banking functions and products, providing opportunities to build data pipelines and reporting capabilities for functional areas such as finance and business management, treasury operations, financial crime prevention, regulatory reporting and analytics. We collaborate with product teams such as card payments, electronic payments, lending,
 
customer onboarding, core banking, and insurance to understand their product datamodels and deliver tailored data solutions that meet business needs. 
 
<div>Job responsibilities
 
<ul><li>Deliver end-to-end data pipeline solutions on cloud infrastructure leveraging the
</li></ul>latest technologies and the best industry practices
 
<ul><li>Use domain modelling techniques to allow us to build best in class business
</li></ul>products.
 
<ul><li>Structure software so that it is easy to understand, test and evolve.
</li><li>Build solutions that avoid single points of failure, using scalable architectural
</li></ul>patterns.
 
<ul><li>Develop secure code so that our customers and ourselves are protected from
</li></ul>malicious actors.
 
<ul><li>Promptly investigate and fix issues and ensure they do not resurface in the future.
</li><li>Make sure our releases happen with zero downtime for our end-users.
</li><li>See that our data is written and read in a way that's optimized for our needs.
</li><li>Keep an eye on performance, making sure we use the right approach to identify
</li></ul>and solve problems.
 
<ul><li>Ensure our systems are reliable and easy to operate.
</li><li>Keep us up to date by continuously updating our technologies and patterns.
</li><li>Support the products you've built through their entire lifecycle, including in
</li></ul>production and during incident management 
 
</div><div>Required qualifications, capabilities &amp; skills 
<ul><li>Formal training or certification on data engineering concepts and applied
</li></ul>experience
 
<ul><li>Recent hands-on professional experience as a data engineer
</li><li>Experience in coding in a recent version of the Python programming language
</li><li>Experience in designing and implementing effective tests (unit, component,
</li></ul>integration, end-to-end, performance, etc.)
 
<ul><li>Excellent written and verbal communication skills in English
</li><li>Experience with cloud technologies and distributed systems
</li><li>Experience with data transformation frameworks and data pipeline orchestration
</li></ul>tools
 
<ul><li>Experience with managing large volumes of data and optimizing data processing
</li><li>Understanding of event-base architecture, data streaming and messaging
</li></ul>frameworks
 
<ul><li>Coach other team members on coding practices, design principles, and
</li></ul>implementation patterns that lead to high-quality maintainable solutions.
 
<ul><li>Manage stakeholders and effectively prioritize work across multiple work
</li></ul>streams. 
 
</div><div>Preferred qualifications, capabilities &amp; skills
 
<ul><li>Experience in working in a highly regulated environment / industry
</li><li>Experience with AWS cloud technologies
</li><li>Experience with data governance frameworks
</li><li>Understanding of incremental data processing and versioning
</li><li>Understanding of RESTful APIs and web technologies 
</li></ul></div>#ICBEngineering #ICBCareers
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
 
 
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.</div>

Lead Data Engineer — International Consumer Bank (Chase UK)

Morgan Stanley

<div>We're seeking someone to join our Investment Banking &amp; Global Capital Markets Technology team as a Vice President in the Advisory Sales &amp; Distribution Super Department to build innovation solutions to support the complex and evolving needs of our businesses in Institutional Securities Group.
In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. 
 
This is a Lead Data &amp; Analytics Engineering position at VP Level, which is part of the job family responsible for providing specialist data analysis and expertise that drive decision-making and business insights as well as crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI-based techniques.
Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.
 
 
What you'll do in the role:
<ul><li>Build out data platform using Snowflake DBaaS platform to enable the business to gain insights across multiple datasets around Client Coverage.
</li><li>Drive the data warehousing architecture &amp; transformation from raw data to published layer for use by development teams and business users.
</li><li>Integrate both internal Client / Deals / CRM / Revenue / AUM / Expenses data and external market data from S&amp;P / LSEG / Equilar / Pitchbook and other vendors to enrich and power next best actions around our clients and contacts.
</li><li>Collaborate with business product owners, software development engineers and data engineering professionals.
</li><li>Communicate progress, challenges, and milestones to senior leadership.
</li><li>Collaborate with stakeholders to prioritize projects and allocate resources effectively.
</li><li>Provide strategic direction for data engineering initiatives and roadmap.
</li><li>Develop and oversee the data engineering budget and resource planning.
</li><li>Ensure compliance with data security, privacy, and regulatory requirements.
</li><li>Foster a collaborative and inclusive team environment to drive innovation and high performance.
</li></ul>What you'll bring to the role:
<ul><li>Proven track record of designing and implementing complex data solutions using the Snowflake DBaaS platform including schema creation, data sharing, row &amp; column level security / masking.
</li><li>Strong SQL query and data modelling skills.
</li><li>Experience with designing and building data warehouses for business intelligence.
</li><li>Experience data ingestion pipelines and Snowflake dynamic tables.
</li><li>Strong data &amp; software development skills with Python, Git and SDLC lifecycle.
</li><li>Proven ability to oversee end-to-end data processes from ingestion to consumption.
</li><li>Strong background in data governance, metadata management, and data lineage.
</li><li>Demonstrated success in aligning data strategies with business objectives.
</li><li>Excellent leadership and decision-making skills to drive business outcomes.
</li><li>Effective communication with stakeholders to define project requirements and priorities.
</li><li>Ability to use tools like Microsoft Power BI / Jupyter Notebooks to rapidly prototype new concepts.
</li><li>At least 8 years' relevant experience would generally be expected to find the skills required for this role.
</li></ul>#LI-FT1 
 
WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
At Morgan Stanley, we raise, manage and allocate capital for our clients &ndash; helping them reach their goals. We do it in a way that&rsquo;s differentiated &ndash; and we&rsquo;ve done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren&rsquo;t just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you&rsquo;ll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There&rsquo;s also ample opportunity to move about the business for those who show passion and grit in their work.
To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.
Certified Persons Regulatory Requirements:
 
If this role is deemed a Certified role and may require the role holder to hold mandatory regulatory qualifications or the minimum qualifications to meet internal company benchmarks.
 
 
Flexible work statement
 
Interested in flexible working opportunities? Morgan Stanley empowers employees to have greater freedom of choice through flexible working arrangements. Speak to our recruitment team to find out more.
 
 
Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.
Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.
For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo .</div>

Lead Data Warehousing Engineer

Worldpay

<div>Ready to take your career global?
Make your mark at one of the biggest names in payments. We&rsquo;re looking for a Senior Data Scientist/Engineer &ndash; Commercial Optimisation to join our ever evolving Global SMB team and help shape the future of global commerce.
What you&rsquo;ll own<ul><li>
Utilize advanced data analytics and machine learning techniques to identify high-value prospects and generate leads in the payments industry.</li><li>
5 + years experience working as a Data Scientist and Data Engineer.</li><li>
Design and implement propensity models to predict potential client engagement and conversion rates, optimizing our prospecting strategies.</li><li>
Analyse transactional and financial data to uncover trends and insights that inform targeted marketing and sales strategies.</li><li>
Identify and evaluate new data sources (internal and external) to support and drive improvements in predictive models</li><li>
Work closely with the marketing and sales teams to refine lead qualification processes, enhance lead scoring models, and streamline lead generation efforts.</li><li>
Develop and maintain Python/SQL-based automated workflows for efficient data preparation, modelling and execution of marketing/prospecting strategies.</li><li>
Present data-driven insights and recommendations to stakeholders to drive strategic decisions and new business initiatives.</li><li>
Continuously monitor the effectiveness of lead generation strategies and adjust models and approaches based on performance data and market feedback.</li></ul>
What you'll bring<ul><li>
Proven experience in data science with a focus on targeted marketing, lead generation and new business development</li><li>
Expert in Python and SQL and experience with data preparation, cleaning, and modelling</li><li>
Expertise in building and deploying machine learning models, especially related to customer behaviour, segmentation, and propensity analysis.</li><li>
Excellent analytical and problem-solving abilities, with a track record of translating data insights into successful business outcomes.</li><li>
Entrepreneurial mindset with the ability to operate in a fast-paced environment and contribute to multiple projects with varying deadlines.</li><li>
Bachelor&rsquo;s or master&rsquo;s degree in Statistics, Mathematics, Computer Science, Finance, or a related field.</li></ul>
About the team
As a forward-thinking finance company based in London, we specialize in innovative payment solutions aimed at streamlining and enhancing the payment processes for businesses and consumers. Our mission is to revolutionize the payments industry by leveraging cutting-edge technology and data-driven insights to foster financial inclusion and efficiency. Join our dynamic team and play a crucial role in driving new business generation and shaping the future of payments.
We are in search of a Senior Data Scientist/Engineer with a strong background in finance and a knack for new business generation. This role is pivotal for our lead generation and prospecting efforts, using advanced analytics and machine learning to identify and engage potential clients in the payments sector. The ideal candidate will possess a unique blend of technical data skills, business acumen, and an entrepreneurial spirit to drive growth and expand our market presence.
What makes a Globalpayer?
Globalpayers think like a client, act like an owner and win as one team. We&rsquo;re curious and innovative &ndash; always finding better ways to deliver impact. We empower each other to make decisions, and it&rsquo;s our passion that drives excellence in everything we set out to do.
Does this sound like you? Then you sound like a Globalpayer. Apply now to take your career global.
To find out more about working with us, find us on LinkedIn.
#LI-AB1</div>

Senior Data Scientist/Engineer - Commercial Optimisation

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