Data Engineer

EXL
Northampton
1 week ago
Create job alert

EXL (NASDAQ: EXLS) is a global data and AI company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. Bringing together domain expertise with robust data, powerful analytics, cloud and AI to create agile, scalable solutions and execute complex operations for the world’s leading corporations.


EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect, creating value from data to ensure faster decision-making and transforming operating models. Key industries include Insurance, Healthcare, Banking and Financial Services, Media, and Retail, among others.


Headquartered in New York, our team is over 60,000 strong, with more than 50 offices spanning six continents. For information, visit www.exlservice.com.


Location: Northampton, United Kingdom


Employment Type: Permanent


We are seeking a highly skilled AWS Data Engineer to design, build and maintain scalable cloud-based data platforms within our Banking and Financial Services portfolio.


This role focuses on developing robust data pipelines, data lakes and data warehouse solutions that enable reliable analytics, reporting and data-driven decision-making. The successful candidate will work across data ingestion, transformation and modelling while ensuring data quality, governance and performance across distributed cloud environments.


You will collaborate closely with data scientists, analytics teams and engineering stakeholders to deliver modern, scalable data solutions within complex enterprise environments.


Experience within the Banking or Financial Services domain is strongly preferred, with exposure to financial datasets, regulatory considerations and enterprise data governance frameworks.


As part of your duties, you will be responsible for:

  • Design, build and maintain scalable data pipelines and ETL/ELT processes using modern cloud data engineering practices
  • Develop and optimise data lake and data warehouse architectures on AWS
  • Ensure high standards of data quality, governance, security and accessibility across data platforms
  • Develop scalable data transformation logic using Python, SQL and Spark-based frameworks
  • Monitor pipeline performance and troubleshoot data workflows to ensure reliability and efficiency
  • Work closely with data scientists, analysts and engineering teams to support advanced analytics and reporting initiatives
  • Implement best practices for data modelling, metadata management and data lineage
  • Produce technical documentation including data architecture, pipeline design and data flow diagrams
  • Support continuous improvement of data platforms through optimisation, automation and performance tuning

Qualifications and experience we consider to be essential for the role:

  • 8+ years of experience in data engineering or data platform development within enterprise environments
  • Strong expertise in AWS data services (such as S3, Glue, Redshift, EMR, Athena, Lambda or similar)
  • Strong programming experience with Python and SQL
  • Hands‑on experience with Spark or distributed data processing frameworks
  • Proven experience building and maintaining data pipelines, data lakes and data warehouses
  • Strong understanding of data modelling, metadata management and data governance principles
  • Experience working with large‑scale distributed data systems and high‑volume datasets
  • Familiarity with CI/CD, version control (Git) and modern development practices
  • Experience working in Agile delivery environments
  • Experience within the Banking or Financial Services domain, including exposure to financial data models, regulatory environments or transaction data
  • Knowledge of Enterprise Data Management (EDM) frameworks
  • Experience with data governance, lineage and metadata management tools
  • Exposure to multi‑cloud environments (Azure or GCP)
  • Experience supporting advanced analytics, machine learning or AI data platforms

As part of a leading global analytics and digital solutions company, you can look forward to:

  • A competitive salary with a generous bonus, private healthcare, critical illness life assurance at 4 x your annual salary, income protection insurance, and a rewarding pension.
  • EXL provides everyday financial well-being solutions, such as cash back cards, in which you can earn cashback while enjoying discounts, promotions, and offers from top retailers. We also offer a Cycle Scheme where you can save money on bikes and cycling accessories.
  • At EXL, we are committed to providing our employees with the tools and resources they need to succeed and excel in their careers. We offer a wide range of professional and personal development opportunities. We also support a range of learning initiatives that allow our employees to build on their existing skills and knowledge. From online courses to seminars and workshops, our employees have the opportunity to enhance their skills and stay up to date with the latest trends and technologies.
  • As an Equal Opportunity Employer, EXL is committed to diversity. Our company does not discriminate based on race, religion, colour, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, age, or disability status.
  • EXL employees are eligible to purchase stock as part of our Employee Stock Purchase Plan (ESPP).
  • At EXL, we offer a flexible hybrid working model that allows employees to live a balanced, healthy lifestyle while strengthening our culture of collaboration.

To be considered for this role, you must already be eligible to work in the United Kingdom.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.