We're recruiting for an experienced Azure Databricks Engineer to join a growing data team. You'll be responsible for designing, developing and supporting scalable data solutions across Azure and Databricks, helping to deliver reliable, high-quality data for the business. This role would require you to be onsite 4 days per week with the final day being remote.
Key Responsibilities
Develop Databricks solutions using SQL, PySpark and Python.
Build and maintain ETL/ELT pipelines across Azure, SQL Server and Databricks.
Support Lakeflow pipelines, production jobs and data quality processes.
Monitor, troubleshoot and optimise data workflows and platform performance.
Work with Delta Lake, Unity Catalog and modern data lake architectures.
Integrate Azure services including ADLS, Data Factory, Key Vault and REST APIs.
Support CI/CD deployments and Databricks automation.
Requirements
Strong hands-on experience with Azure Databricks in an enterprise environment.
Excellent SQL Server/T-SQL and data engineering skills.
Experience building and optimising large-scale data pipelines.
Knowledge of Spark, Delta Lake, Unity Catalog and Azure data services.
Exposure to Git, CI/CD and infrastructure automation tools.
Strong communication skills and a proactive approach to problem solving.
Desirable
Databricks certifications.
Experience with Microsoft Fabric, MLflow or Terraform.
Background working on enterprise data warehouse or data lake projects.
If this Data Engineer role sounds like a good fit, you can work 4 days per week on site in London and you’d like to know more, please apply with your most up-to-date CV and I’ll be in touch.