At a Glance
- Tasks: Lead the design and delivery of ETL data flows for a major banking client.
- Company: Join EXL, a global leader in data and AI solutions.
- Benefits: Flexible hybrid working, competitive pay, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and excellence.
- Why this job: Make a real impact on regulatory data solutions in a dynamic banking environment.
- Qualifications: Experience in data engineering, especially with IBM DataStage and Oracle.
The predicted salary is between 72000 - 88000 £ per year.
EXL (NASDAQ: EXLS) is a global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 60,000 employees spanning six continents.
We are seeking an experienced Lead Data Engineer to join a major banking client working on their Risk Data Warehouse (RDW) platform. This role is critical to supporting both ongoing regulatory change initiatives and the stability of production data pipelines underpinning key risk and finance reporting.
You will act as a hands-on technical lead, driving the design and delivery of end-to-end ETL data flows using IBM DataStage and Oracle, ensuring high-quality, controlled, and auditable data pipelines aligned to regulatory standards (including Basel 3.1 and credit risk programmes).
As part of your duties, you will be responsible for:
- Lead the design, build, and validation of ETL pipelines supporting the Risk Data Warehouse
- Make and document ETL and data flow design decisions, ensuring traceability and regulatory compliance
- Deliver high-quality data pipelines supporting Basel 3.1, Murex migration, and credit risk reporting
- Define and implement data lineage, controls, and validation frameworks
- Provide hands-on technical leadership across DataStage and Oracle development
- Collaborate with risk, trading, and engineering stakeholders to gather and translate requirements into scalable data solutions
- Act as the primary escalation point for critical RDW incidents, including triage, root cause analysis, and resolution
- Produce production-ready artefacts (monitoring, runbooks, failure handling, support documentation)
- Drive continuous improvement through post-incident reviews and corrective actions
Qualifications and experience we consider to be essential for the role:
- Strong experience as a Senior / Lead Data Engineer within banking or financial services
- Proven background delivering regulatory data solutions (e.g. Basel, credit risk, capital reporting)
- Deep expertise in IBM DataStage and Oracle (PL/SQL, data warehousing)
- Experience working on Risk Data Warehouse or similar enterprise data platforms
- Strong understanding of data lineage, governance, and control frameworks
- Experience integrating risk data flows with trading / risk systems (e.g. Murex or similar)
- Demonstrated ability to operate in hands-on delivery roles, leading engineering teams and solving complex technical challenges
To be considered for this role, you must already be eligible to work in the United Kingdom.
Lead Data Engineer employer: EXL
EXL is an exceptional employer that fosters a dynamic and inclusive work culture, offering employees the chance to thrive in a fast-paced fintech environment. With a strong focus on professional development, team collaboration, and innovative problem-solving, employees are empowered to grow their skills while contributing to meaningful projects in regulatory reporting and compliance. The remote working flexibility allows for a balanced lifestyle, making EXL an attractive choice for those seeking rewarding career opportunities in the UK.
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We think this is how you could land Lead Data Engineer
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Lead Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at EXL, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at EXL. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at EXL
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at EXL!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
