Databricks Data Engineer

Azure Databricks Data Engineer Location: London Working pattern: Hybrid – 3–4 days per week onsite Contract: Inside IR35 Role Overview We are looking for an experienced Azure Databricks Data Engineer to design, develop and deliver scalable data solutions within an HR technology environment. You will work across the employee lifecycle, building reliable data pipelines and analytics solutions with a strong focus on automation, testing, security and production quality. Key Responsibilities • Design and develop scalable data pipelines and analytics solutions using Azure Databricks and Azure Data Factory. • Build and improve data products supporting HR and employee lifecycle processes. • Translate business and technical requirements into production-ready solutions. • Develop data lake, data warehouse and data mesh solutions using Azure services. • Work with large, complex and multi-format datasets. • Apply automated testing, CI/CD and DevOps practices throughout the development lifecycle. • Build observability into solutions to monitor production health and support incident resolution. • Ensure solutions meet security, reliability, compliance and performance standards. • Collaborate with engineering, product, HR and other cross-functional teams. • Contribute to technical decisions with long-term scalability and sustainability in mind. Essential Skills and Experience • 8–10 years of hands-on data engineering experience. • Strong commercial experience with Azure Databricks and Azure Data Factory. • Advanced Spark development using Python or Scala, alongside strong SQL skills. • Experience with Azure Data Lake Storage Gen2 and Azure SQL or PostgreSQL. • Strong understanding of Azure analytics services and Azure identity, including SPN, SAMI and UAMI. • Experience designing data lake, data warehouse, data mesh and service-oriented integration solutions. • Previous ETL development experience using Informatica, SSIS, Talend or similar. • Experience delivering solutions within an Agile SDLC environment. • Strong Git, GitLab or GitHub experience, including branching, pull requests and CI/CD. • Hands-on scripting experience with Linux or PowerShell. • Exposure to Docker and automated testing practices. • Experience with pipeline orchestration tools such as Apache Airflow, Autosys or Control-M, with Airflow preferred. • Excellent written and verbal English communication skills. Desirable Skills • Kafka or other streaming technologies. • Terraform, ARM templates, YAML or Puppet. • GitLab CI/CD pipeline creation. • Azure Functions and Logic Apps. • Test-driven development.