Senior Data Engineer

Opus Recruitment Solutions Limited; Nottingham; On-site; GBP 60,000 - 80,000; Full time

Job summary

Opus Recruitment Solutions Limited is seeking an experienced Data Engineer to design, build, and optimise data platforms in an Azure Databricks environment.

You will develop scalable data pipelines, manage large datasets, and deliver high-quality data solutions within a modern cloud data stack. The role requires hands-on expertise in Python, PySpark, SQL, and Spark SQL, with a focus on orchestration, governance, and performance tuning.

Qualifications

• Strong Python, PySpark and SQL/Spark SQL for building production-grade ETL/ELT pipelines.
• Deep knowledge of Apache Spark: DataFrames, joins, partitions, caching, and performance tuning.
• Experience with Azure Databricks, including clusters, notebooks, jobs and Databricks Runtime; Lakehouse architectures on ADLS Gen2.
• Familiarity with CDC, Auto Loader, batch processing, and modern ingestion patterns; Lakeflow integration and Unity Catalog awareness.

Skills

Python

PySpark

SQL

Spark SQL

Apache Spark

Azure Databricks

Lakehouse

CDC

Git

Azure DevOps

Kafka

Streaming data

Kimball

Job description

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.