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For Companies At a Glance
- Tasks: Lead data transformation projects and solve complex data challenges across teams.
- Company: Major UK organisation focused on innovative data solutions.
- Benefits: Competitive daily rate, hybrid working, and long-term contract.
- Why this job: Shape the future of data architecture and make impactful decisions.
- Qualifications: Strong data engineering experience and advanced SQL skills required.
- Other info: Dynamic environment with opportunities for ownership and growth.
A major UK organisation is undertaking a large-scale data warehouse re-architecture and migration programme and is looking for a Lead Analytics Engineer to join on a long-term contract. This is a hands-on, highly cross-functional role where you will work across multiple business and technical teams to solve complex data problems. You will play a key role in shaping the next generation of data assets, helping move from legacy architecture to a simpler, more scalable, and analytics-friendly platform.
This programme is not a lift-and-shift migration. It focuses on rethinking how data is modelled, accessed, and used, with an emphasis on clarity, scalability, and enabling faster, better decision-making. We are particularly interested in individuals who have thrived in less structured, fast-moving environments—where ownership, problem-solving, and adaptability are critical.
What You’ll Do
- Work across multiple teams and business domains to understand problems and deliver effective data solutions
- Design and build scalable, well-structured data models in a modern warehouse environment
- Translate complex requirements into clear, maintainable SQL-based transformations
- Lead data migrations, including historical backfills and zero-downtime cutovers
- Collaborate closely with Analytics Engineers, Data Scientists, Product, and Engineering teams
- Help define and evolve data standards, modelling approaches, and best practices
- Enable teams by delivering high-quality, trusted datasets that are easy to use and understand
- Clearly articulate trade-offs in tooling and design decisions, explaining not just what to use, but why
Technical Environment
- dbt (SQL-first modelling)
- Airflow orchestration
- BigQuery (or similar cloud data warehouse such as Snowflake)
- Data sourced from transactional, operational, and product systems
- Mix of open-source, cloud, and internal tooling
Required Experience
- Strong experience in data modelling, ETL/ELT, and building scalable data pipelines
- Advanced SQL skills and deep understanding of data warehousing principles
- Experience working with large-scale datasets
- Hands-on experience with dbt and modern data stack tooling
- Experience designing data solutions that support analytics and reporting use cases
- Background can be from any industry (not limited to financial services), provided strong data engineering/analytics experience
What We’re Looking For
- Experience working in dynamic, less structured environments (e.g. startups, scale-ups, or transformation programmes)
- Strong cross-functional mindset—comfortable working across teams to solve problems
- Ability to rationalise technical decisions, clearly explaining the reasoning behind tools and approaches
- Excellent stakeholder management skills, with the ability to influence both technical and non-technical audiences
- Clear, concise communicator—able to explain complex ideas simply and effectively
- Proactive, adaptable, and comfortable taking ownership in ambiguous situations
Data Engineer in Southampton employer: iDPP
Contact Detail:
iDPP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Southampton
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. Attend meetups or webinars related to data analytics to meet potential employers and learn about openings that might not be advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving SQL transformations and data modelling. This will give you an edge when discussing your experience with hiring managers and demonstrate your hands-on capabilities.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Be ready to discuss how you've tackled complex data challenges in the past, and think about how you can articulate your thought process clearly to both technical and non-technical audiences.
✨Tip Number 4
Don't forget to apply through our website! We have loads of opportunities that might be perfect for you. Plus, applying directly can sometimes give you a better chance of getting noticed by recruiters who are looking for candidates just like you.
We think you need these skills to ace Data Engineer in Southampton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Engineer. Highlight your experience with data modelling, ETL/ELT, and any hands-on work with dbt or cloud data warehouses like BigQuery. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Share specific examples of how you've thrived in fast-paced environments and tackled complex data problems. We love a good story!
Showcase Your Problem-Solving Skills: In your application, don't just list your skills—show us how you've used them to solve real-world problems. Whether it's designing scalable data models or leading migrations, we want to know how you’ve made an impact in previous roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Plus, it’s super easy to do!
How to prepare for a job interview at iDPP
✨Know Your Data Inside Out
Before the interview, make sure you’re well-versed in data modelling and ETL/ELT processes. Brush up on your SQL skills and be ready to discuss how you've built scalable data pipelines in the past. Being able to articulate your experience with tools like dbt and BigQuery will show that you’re not just familiar with the tech, but that you can leverage it effectively.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data problems in less structured environments. Think about specific challenges you faced, the solutions you implemented, and the impact they had. This will demonstrate your adaptability and ownership, which are key traits for this role.
✨Communicate Clearly and Concisely
Practice explaining complex data concepts in simple terms. You might be asked to explain your thought process behind certain technical decisions, so being able to communicate clearly with both technical and non-technical audiences is crucial. Use analogies or real-world examples to make your points relatable.
✨Collaborate and Engage
Since this role involves working across multiple teams, be prepared to discuss how you’ve collaborated with different stakeholders in the past. Highlight your experience in influencing decisions and how you’ve helped teams understand data standards and best practices. Showing that you can work well with others will set you apart.