At a Glance
- Tasks: Build and scale a data platform for national economic analysis using Azure Databricks.
- Company: Join a forward-thinking team making impactful decisions at a national level.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on quality and governance in data management.
- Why this job: Make a real difference by engineering solutions that inform critical economic decisions.
- Qualifications: 8+ years in data engineering with strong skills in Azure Databricks, Python, and SQL.
The predicted salary is between 63000 - 77000 £ per year.
Build the data platform behind national economic analysis. We are hiring a Senior Data Engineer to develop and scale an Azure Databricks platform that powers monetary analysis, economic forecasting and modelling. The data you engineer feeds the models that inform decisions at a national level, so quality, lineage and reliability genuinely matter here. This is hands-on engineering, not oversight. You will own pipelines end to end, from ingestion through transformation to governed, production-ready datasets used daily by economists and data scientists.
What you will be doing:
- Designing and building scalable ingestion pipelines from APIs, relational databases and financial data providers into Azure Databricks
- Writing complex transformations in PySpark and Spark SQL, with Delta Lake as the storage foundation
- Tuning Databricks workloads for performance and cost, and embedding quality checks and validation into every pipeline
- Implementing governance in practice: Unity Catalog, Azure Purview, data lineage, metadata and monitoring
- Automating deployments through CI/CD in Azure DevOps and promoting DevOps practice across the team
- Working directly with economists and data scientists to turn analytical requirements into engineered solutions
What we need from you:
- 8+ years in data engineering, including 3+ years hands-on with Azure Databricks
- Strong Python and PySpark, backed by advanced SQL
- Deep grounding in data warehousing, data modelling and integration patterns
- Unity Catalog and Delta Lake in a production environment
- Data quality and governance experience, ideally including Azure Purview
- Git, Agile delivery and a collaborative approach to code review
- Active SC clearance. This is a firm requirement and we are unable to sponsor or process new clearance for this role
Nice to have:
- Streaming experience with Kafka or Azure Event Hubs
- Azure Data Engineer Associate or Databricks certification
- Docker, Kubernetes, Terraform or infrastructure as code
Why this role:
You get a modern, well-funded Azure estate, a mandate to build it properly rather than patch it, and work with real public significance. Hybrid working, three days on site in central London.
Senior Data Engineer in London employer: Intelstack
As a leading employer in the tech industry, we offer a dynamic work environment that fosters innovation and collaboration. Our hybrid work model allows for flexibility while our commitment to employee growth ensures that you will have access to continuous learning opportunities and career advancement. Located in a vibrant area, we provide a supportive culture that values diversity and encourages meaningful contributions to impactful projects.
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We think this is how you could land Senior Data Engineer in London
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We think you need these skills to ace Senior Data Engineer in London
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 Intelstack. 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 Intelstack
✨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
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✨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.
