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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 Coventry employer: iDPP
Contact Detail:
iDPP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Coventry
✨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 get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best data projects, especially those that highlight your experience with SQL, dbt, and data modelling. This will give you an edge when chatting with hiring managers and help them see what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Think about how you've tackled complex data problems in the past and be ready to share those stories. Remember, they want to see how you think and solve issues!
✨Tip Number 4
Don't forget to apply through our website! We have loads of exciting opportunities that might just be the perfect fit for you. Plus, applying directly shows your enthusiasm and commitment to joining our team.
We think you need these skills to ace Data Engineer in Coventry
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience with data modelling, ETL/ELT, and any relevant tools like dbt or 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 hear about your hands-on experience and the impact you've made.
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—just a few clicks and you’re done!
How to prepare for a job interview at iDPP
✨Know Your Data Inside Out
Make sure you’re well-versed in data modelling, ETL/ELT processes, and SQL. Brush up on your experience with dbt and cloud data warehouses like BigQuery or Snowflake. Being able to discuss specific projects where you've built scalable data pipelines will really impress.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data problems in less structured environments. Highlight your adaptability and ownership in these situations. Companies love candidates who can think on their feet and come up with innovative solutions.
✨Communicate Clearly and Concisely
Practice explaining complex technical concepts in simple terms. You’ll likely need to communicate with both technical and non-technical stakeholders, so being able to articulate your thoughts clearly is key. Use real-life examples to demonstrate your communication skills.
✨Understand the Business Context
Research the organisation and its data needs. Be ready to discuss how your role as a Data Engineer can help shape their data assets and improve decision-making. Showing that you understand their business challenges will set you apart from other candidates.