At a Glance
- Tasks: Lead data engineering teams and shape innovative solutions for clients.
- Company: Capgemini, a diverse and inclusive tech leader.
- Benefits: Hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Join a dynamic team focused on innovation and sustainability.
- Why this job: Make a real impact in shaping the future of data engineering.
- Qualifications: Experience in data engineering and strong leadership skills required.
The predicted salary is between 66150 - 80850 £ per year.
We are looking for an experienced Lead Data Engineer to help shape and grow our data engineering capability on the south coast, based out of our new Hove office. At Capgemini, it is important to create an environment where individuals and teams are able to take responsibility not just for their assigned tasks, but for the broader success of the programme. Our vision goes beyond providing great IT Services; we're shaping the future together.
This is a senior engineering leadership role within our Data Portfolio. It combines technical leadership, delivery accountability, governance, capability growth and people development, with a particular focus on building a sustainable data engineering presence in Hove. This role will need you to be client centric - to put the client's needs, goals and ambitions at the heart of everything you do. Actively seek to understand what success looks like for the client and shape your work to help them achieve it. Going the extra mile will also be imperative. Acting as a true partner - anticipating needs, solving problems and helping the client achieve their goal.
The Hove office is an important growth location for Capgemini. Today, our south coast team has a strong legacy technology heritage, with smaller pockets of modern data work. We want to build on that foundation and create a broader, modern data engineering capability. Working with senior portfolio leadership, delivery teams and the wider Insights & Data engineering practice, you will take ownership for shaping and assuring engineering outcomes delivered by the Portfolio, with a focus on the Hove-based teams. We anticipate candidates spending 40-70% of their time in our Hove office to help build local relationships, support people development, and shape the business growth needed to establish a stronger data engineering presence.
Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
If you are successfully offered this position, you will go through a series of pre-employment checks, including: identity, nationality (single or dual) or immigration status, employment history going back 3 continuous years, and unspent criminal record check (known as Disclosure and Barring Service).
Your role:
- Lead Hove-based data engineering teams and wider in shaping solution direction, delivery approaches, engineering standards and technical outcomes.
- Own local engineering delivery assurance, governance, design reviews and assuring commercially sound technical decisions.
- Actively grow the Hove-based capability through recruitment, junior talent programmes, onboarding, mentoring, and community engagement – taking ownership for Hove but working with our wider team to achieve this.
- Shape the modernisation of a mixed estate, bringing pragmatic leadership across legacy systems, cloud platforms and contemporary data engineering practices.
- Build trusted relationships with client, partner and internal stakeholders, bringing clarity, ownership and constructive challenge to complex technical and delivery decisions.
- Identify and shape opportunities for growth, including new work, capability development, bid support and stronger use of data engineering capability across the wider Insights & Data Practice.
Your skills and experience:
- Strong experience as a senior data engineer or engineering lead, with a track record of owning complex data delivery across multiple teams, projects or programmes.
- A collaborative leadership style, with experience mentoring, coaching, recruiting or developing engineers and helping teams work as part of a wider engineering community.
- Deep data engineering knowledge across integration, transformation, orchestration, modelling, quality, observability, performance, security and operational support.
- Credibility across modern data platforms and cloud technologies, alongside the pragmatism needed to work in large enterprise and legacy environments.
- Experience setting, governing and improving engineering standards, quality controls, reusable patterns and delivery processes.
- Strong stakeholder management, with the ability to explain complex technical issues clearly and build trust with senior clients and internal leaders.
- Commercial awareness, including the ability to make engineering decisions that balance quality, cost, maintainability, profitability, delivery confidence and client satisfaction.
Technical landscape: We work across a broad and evolving technology landscape, so we are looking for strong data engineering fundamentals and credible technical depth rather than a perfect match against every tool. Programmes of work being delivered include large scale data migrations to cloud, new project delivery, service enhancement and support. Relevant experience may include:
- Strong SQL and data modelling experience.
- ETL/ELT design and delivery.
- Data pipeline design, build, monitoring and operations.
- Batch and real-time data integration patterns.
- AWS cloud data platforms.
- Data lake, lakehouse, warehouse or large-scale analytical platform delivery.
- Python, Bash or other scripting and automation approaches.
- Workflow orchestration and scheduling tools, such as Airflow, TWS, JS7 or similar.
- CI/CD, version control and modern engineering delivery practices.
- Data quality, testing, observability and operational resilience.
- Working with enterprise platforms such as Oracle, Cloudera, SAS, Denodo, Power BI or similar technologies.
This role goes beyond leading delivery. Successful candidates will be expected to take clear ownership for the capability, quality and engineering outcomes of Hove-based work, while helping shape a positive engineering culture across our Hove office, the wider Data Portfolio and the Insights & Data Practice.
Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who declare they have a disability and meet the minimum essential criteria for the role. Please opt in during the application process.
Your security clearance: To be successfully appointed to this role, it is a requirement to obtain Security Check (SC) clearance. To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements. Throughout the recruitment process, you will be asked questions about your security clearance eligibility such as, but not limited to, country of residence and nationality. Some posts are restricted to sole UK Nationals for security reasons; therefore, you may be asked about your citizenship in the application process.
Why you should consider Capgemini: Growing clients’ businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you’ll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what’s possible. It’s why, together, we seek out opportunities that will transform the world’s leading businesses, and it’s how you’ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you’ll build the skills you want. You’ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.
About Capgemini: Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.5 billion.
Lead Data Engineer employer: Capgemini
Capgemini is an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of London. With a hybrid working model, employees enjoy the flexibility of blending office, client site, and home working, while also benefiting from extensive growth opportunities and professional development within the Capital Markets sector. Join us to be part of a team that values governance excellence and empowers you to make a meaningful impact in complex programme environments.
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We think this is how you could land Lead Data Engineer
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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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Capgemini. 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 Capgemini
✨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!
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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 Capgemini!
✨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.