Senior Data Engineer
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Summary
Senior Data Engineer designing and building modern data platforms on Azure: developing scalable ETL/ELT pipelines with Python, PySpark and Spark SQL in Azure Databricks, implementing Bronze/Silver/Gold lakehouse layers on ADLS Gen2, with Unity Catalog governance, Lakeflow orchestration and Kafka/CDC streaming. Hybrid role: 3 days per week on site in Nottingham.
We're looking for an experienced Data Engineer with strong Azure Databricks expertise to support the design, development, and optimisation of modern data platforms. You'll be responsible for building scalable data pipelines, managing large datasets, and delivering high-quality data solutions within an Azure environment.
Key Skills & Experience Required
- Strong hands‑on experience with Python, PySpark, and SQL/Spark SQL for building production‑grade ETL/ELT pipelines
- Solid knowledge of Apache Spark, including DataFrames, joins, aggregations, partitioning, caching, and performance optimisation
- Experience working within Azure Databricks, including clusters, job clusters, notebooks, repositories, jobs, and Databricks Runtime
- Proven experience implementing Lakehouse architectures, including Bronze, Silver, and Gold data layers on Azure Data Lake Storage Gen2
- Familiarity with modern data ingestion approaches, including Auto Loader, batch processing, incremental loads, and Change Data Capture (CDC)
- Experience orchestrating workflows using Lakeflow Jobs and Lakeflow Pipelines
- Working knowledge of Unity Catalog, including schemas, tables, access controls, and data governance best practices
- Experience with Git‑based version control and CI/CD processes, ideally using Azure DevOps
- Experience with Kafka and real‑time or streaming data solutions
- Exposure to Debezium and CDC frameworks
- Knowledge of Kimball dimensional modelling and enterprise data warehouse design principles
You can work 3 days per week on site in Nottingham.