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We are looking for an experienced Senior Databricks Data Engineer to join its data and technology environment and contribute to the development and modernisation of enterprise data platforms.
The role requires a strong hands-on engineer with deep experience in Databricks, Python/PySpark and SQL, capable of designing and building scalable data pipelines and transforming complex data from multiple business systems into reliable, analytics-ready datasets.
You will work closely with data engineers, analysts, architects and business stakeholders to deliver robust data solutions supporting analytics, reporting and broader data-driven initiatives across the organisation.
This is a senior hands-on position requiring both strong engineering capability and the ability to take ownership of technical solutions from design through implementation and production support.
Design, develop and maintain scalable data pipelines and ETL/ELT solutions using Databricks.
Build and optimise data processing workloads using PySpark, Python and SQL.
Develop data solutions using modern Lakehouse architecture principles.
Design and maintain Bronze, Silver and Gold data layers using Medallion Architecture.
Ingest and integrate data from multiple enterprise systems, databases, APIs and other structured and semi-structured sources.
Build reusable and maintainable data transformation frameworks.
Implement data validation, quality checks, error handling and monitoring across data pipelines.
Optimise Databricks workloads for performance, scalability and cost efficiency.
Work with Delta Lake for reliable and performant data storage and processing.
Support data modelling and preparation of curated datasets for analytics, BI and downstream applications.
Implement appropriate data governance, security and access-control practices.
Troubleshoot production data issues and perform root-cause analysis.
Participate in code reviews, testing and deployment processes.
Collaborate with Data Architects, BI/Analytics teams and business stakeholders to translate requirements into technical data solutions.
Contribute to technical standards, engineering best practices and reusable patterns across the data platform.
Mentor and support other engineers where required.
Strong commercial experience as a Data Engineer / Senior Data Engineer, ideally within a large enterprise environment.
Significant hands-on experience with Databricks in production environments.
Advanced PySpark / Apache Spark development experience.
Strong Python programming skills.
Advanced SQL skills, including complex transformations and performance optimisation.
Strong experience designing and developing ETL/ELT data pipelines.
Practical experience with Delta Lake and Lakehouse architecture.
Experience implementing Medallion Architecture (Bronze, Silver, Gold).
Strong understanding of data warehousing and data modelling concepts.
Experience integrating data from multiple heterogeneous source systems.
Understanding of data quality, validation, reconciliation and monitoring approaches.
Experience with CI/CD, Git and automated deployment practices for data engineering workloads.
Experience troubleshooting and optimising large-scale data processing workloads.
Strong understanding of production support, monitoring and operational reliability.
Ability to independently design and deliver data engineering solutions rather than only implementing predefined tasks.
Strong communication and stakeholder collaboration skills.
Experience with Microsoft Azure and Azure Databricks.
Experience with Unity Catalog, including governance, permissions and data lineage.
Experience with Azure Data Factory or similar orchestration technologies.
Exposure to Microsoft Fabric.
Experience with dbt.
Experience building data solutions for Power BI or other enterprise BI platforms.
Experience with enterprise ERP or operational systems such as SAP.
Experience within retail, healthcare, pharmacy, FMCG or other high-volume transactional environments.
Exposure to data governance and enterprise data quality frameworks.
Databricks certifications.
We are looking for a hands-on Senior Data Engineer, not someone whose recent experience is primarily architectural or managerial.
The successful candidate should be comfortable taking ownership of complex Databricks workloads, writing production-grade PySpark, Python and SQL, designing scalable data pipelines and working with large enterprise datasets.
You should be able to understand a business requirement, translate it into an appropriate data engineering solution, implement it and support it in production while maintaining high standards for performance, reliability, data quality and maintainability.