senior software engineer

ai engineer

data engineer

data scientist

machine learning engineer

senior data engineer

HOMETRACK

<div>Hybrid working pattern - 2 days per week from London Bridge Office
Hometrack is seeking an experienced Senior Data Engineer to join our product team to help us deliver Hometrack's Data Services ambitions. By building the best property data sets available, which back the market leading AVM, trusted by 17 out of the top 20 mortgage lenders in the UK, we open the door to helping all our customers make the decisions that matter to them - to buy, to lend, to build.
The Data Services team works with 100s of customers across the property sector ranging from mortgage lenders, house builders, investors, fin &amp; proptech, insurers, telco, retail and utilities, as well as others involved in the housing market. Our mission is to inform decision makers by putting the UK&rsquo;s most trusted property data and insights at the heart of the property ecosystem.
Our market intelligence and customer acquisition, retention and engagement solutions are relied upon by leading industry professionals.
Data Services has a diverse product range covering market, property and mover intelligence, delivered through varying mechanisms including data platforms, reports and APIs, providing maximum flexibility when matching our customers&rsquo; needs to the most effective data solution.
Hometrack is looking for an experienced senior data engineer to help us make this a reality.
What we&rsquo;re looking for in a Senior Data Engineer:<ul><li>
Be accountable for team outcomes, playing your part in achieving team goals and ensuring your contribution positively impacts overall success</li><li>
Be a continual improver, looking for ways to help the team do better and be better, again and again</li><li>
Write maintainable, testable code and enjoy providing code reviews</li><li>
Be experienced with Databricks, Delta Lake and Lakehouse architecture for efficient data management; experience with ETL processes and optimizing data pipelines for performance</li><li>
Be strong in Python, SQL, and PySpark</li><li>
Be passionate about building data products for stakeholders and customers, ensuring they are stable, scalable, secure, accurate, observable, and performant</li><li>
Enjoy collaborating closely with colleagues in Product, Analytics, Security, and Software, explaining technical concepts to non-technical audiences</li></ul></div>

Senior Data Engineer

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>

Codurance

<div>Codurance is a global software consultancy, focused on raising the bar in the software industry through supporting tech communities and working with our clients. We help our clients build remarkable digital products, evolve strategic legacy systems, and equip them to continuously deliver value through the adoption of quality practices and expertise.
We are looking for a Contract Senior Data Engineer who shares our values of craftsmanship, pragmatism, and professionalism. You understand that data engineering is, at its core, great software engineering, applied at scale, with rigour, and with production in mind.
Databricks is our primary data engineering platform, and you will be expected to use it fluently, but the goal is always durable, well-crafted data systems, not tool advocacy.
This is an initial 6-month contract, inside IR35.
What You&rsquo;ll Work On
Our data engineering engagements fall into three primary shapes:<ul><li>
Data Foundations</li><li>
Data Modernisation, re-platforming legacy ETL, introducing automated testing and data contracts, and aligning data models with application domains</li><li>
AI-Ready Data Enablement, preparing data systems to safely support AI and ML use cases, including feature pipelines, scalable compute, and guardrails around data quality and lineage</li></ul>
These engagements sit within wider software modernisation and platform evolution work, not as standalone data projects. You&rsquo;ll work alongside software craftspeople, architects, and client engineers, with data as one part of a broader delivery picture. 
Requirements 
You consider yourself a data engineer with strong software engineering instincts. You care deeply about the quality, testability, and operability of what you build, not just whether it runs.
You are comfortable working in small increments, tightening feedback loops, and letting tests inform your pipeline design. You understand that data systems live in production long after they are first delivered, and you build with that in mind.
You are a team player who values frequent collaboration with software engineers, data scientists, business analysts and client stakeholders alike. You invest in your craft, stay curious about emerging tooling, and are enthusiastic about sharing what you learn.
Data Engineering Practices
You have solid experience applying software engineering disciplines to data: writing testable pipelines, using version control rigorously, and treating data models as first-class software artefacts. You are familiar with data contracts, schema evolution, and the principles of incremental delivery applied to data work.
Platform and Architecture
You have hands-on experience with Databricks and are comfortable across its core capabilities: Delta Lake, Unity Catalog, Databricks Workflows, and notebook-to-production pipeline patterns. You have a working understanding of lakehouse architecture and medallion design, and can articulate trade-offs clearly to clients and colleagues.
Beyond Databricks, experience with the broader data engineering landscape, including tools such as dbt, Apache Spark, and data quality frameworks, is a plus.
Data Engineering for ML and AI
You understand how machine learning and AI systems consume data, and you build the pipelines that feed them to production. You are comfortable with engineering reproducible feature pipelines, managing feature tables in Unity Catalog, and using MLflow for experiment tracking and model registry so that training data and model lineage stay traceable. You prepare and version the datasets that models depend on, and you treat that data with the same rigour you apply to any production system.
You are familiar with the data engineering behind modern AI use cases: building embedding and retrieval pipelines, populating and maintaining vector stores, and assembling the evaluation and ground-truth datasets that make model behaviour measurable.
Software Engineering Foundations
Your data engineering work is grounded in solid software fundamentals. You understand clean code principles, meaningful abstraction, and the difference between code that works and code that can be maintained. You are familiar with CI/CD applied to data pipelines and are comfortable contributing to infrastructure-as-code environments.
Observability and Production Readiness
You understand what it means to run data systems in production. This includes pipeline monitoring, alerting, data quality validation, lineage tracking, and the operational disciplines needed to maintain trust in data over time.
Cloud Platforms
You have experience working on at least one major cloud provider (AWS or Azure) and are comfortable with the infrastructure patterns that underpin modern data platforms. Familiarity with cloud-native services for storage, compute, and orchestration is expected.
Collaboration and Client Engagement
You can work effectively within a client&rsquo;s environment and communicate clearly with both technical and non-technical stakeholders. You understand how to manage expectations, navigate legacy constraints, and make pragmatic decisions under real-world delivery conditions.
Legal / Eligibility
You must be eligible to work in the UK. 
Benefits</div>

Senior Data Engineer (Contract)

duvo.ai

<div>
 
 About The Role
 
 
 
 We already collect a lot of data &mdash; now we need someone to turn it into leverage. This is not a classic pipelines-and-warehouse hire (that's table stakes). It's an AI-native take on the data role: build the foundations, then build the agents and internal workflows on top that make the whole organization faster and more data-driven.
 
 
 What you'll own
 
 
 The data foundation &mdash; pipelines, warehouse, the substrate. Necessary, but not the point.
 
 
 Agents and internal workflows built on top of that foundation &mdash; the actual leverage.
 
 
 Enabling the org (product and beyond) to make faster, data-driven decisions.
 
 
 This is an AI-native, senior role for someone who builds. You'll work across the data substrate and the agentic layer on top of it, and you'll be measured by how much faster and smarter you make the rest of the team.
 
 
 Compensation Range: &euro;135K - &euro;190K
 
 
</div>

Data Engineer (EU/UK Based - Remote)

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

JPMorganChase

<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)

Burns Sheehan

<div>
 
 
 Senior Backend Engineer &ndash; Fintech - Python
 
 
 
 
 
 
 
 📍 London (Hybrid, 3 days per week)
 
 
 
 
 
 
 
 💵 &pound;80,000 &ndash; &pound;90,000 + 10-20% Bonus
 
 
 
 
 
 
 
 💻 Python, Django, Flask, Pandas, APIs, Airflow, Data Processing
 
 
 
 
 
 
 
 📈 Growing Private Credit technology platform
 
 
 
 
 
 
 
 ⚙️ Backend ownership, platform engineering and data-adjacent challenges
 
 
 
 
 
 
 
 
 
 We're partnered with a specialist technology business operating within the Private Credit and Asset Finance space. Following multiple new client wins and a significant increase in platform demand, they're expanding their engineering team with the hire of a Senior Backend Engineer.
 
 
 
 
 
 This is a genuine ownership role within a small, highly capable engineering team. Engineers are responsible for features and components from design through to delivery, working closely with technical leadership and domain experts to shape the future of the platform.
 
 
 
 
 
 The business has built a sophisticated software platform used to manage and monitor complex financial workflows. As new projects continue to onboard, they're looking for an experienced Python engineer to help scale backend services, APIs and data-processing capabilities across the platform.
 
 
 
 
 
 One of the more interesting aspects of the opportunity is the level of influence available. There is no traditional product management layer, meaning engineers have direct input into technical decisions, ownership of meaningful components and the opportunity to shape how the platform evolves.
 
 
 
 
 
 
 Ideal profile:
 
 
 
 &bull; 5+ years' commercial software engineering experience
 
 
 &bull; Strong Python backend development experience
 
 
 &bull; Commercial experience with Django, Flask or similar frameworks
 
 
 &bull; Experience building APIs and backend services in production environments
 
 
 &bull; Comfortable working with data-processing workflows, ETL pipelines or DataFrame-style tooling
 
 
 
 
 
 
 
 
 
 Senior Backend Engineer &ndash; Fintech - Python
 
 
</div>

Senior Software Engineer

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Senior Data Engineer

Senior Data Engineer

Senior Data Engineer (Contract)

Data Engineer (EU/UK Based - Remote)

Lead Data Engineer

Lead Data Engineer — International Consumer Bank (Chase UK)

Senior Software Engineer