Lead/Senior Data Engineer

Role

• Lead the architecture, design and delivery of Data Lake, Data Warehouse and Lakehouse platforms, including on Databricks.
• Own and build scalable, reliable ETL/ELT pipelines and large-scale ingestion from diverse structured and unstructured sources.
• Build and manage data infrastructure on Databricks and modern data stack (Spark, Delta Lake).
• Define and drive data modeling (dimensional, Data Vault), data quality, and data governance standards across Lake and Warehouse layers.
• Optimize data processing jobs and SQL / Spark workloads for performance, reliability and cost on Databricks.
• Implement data security, access control, data lineage and compliance practices.
• Provide technical leadership, mentorship and code reviews to the team.
• Partner with analysts, data scientists and application teams to deliver trusted data products.

Requirements

• Degree in Computer Science, IT, Data Engineering or related.
• 5+ years in data engineering with experience leading projects or small teams.
• Strong in SQL, Python /Scala, and Spark on Databricks.
• Hands-on with Databricks Lakehouse platform, Delta Lake, ETL/ELT frameworks and orchestration (e.g., Airflow / Databricks Workflows).
• Proven experience building and operating Data Lakes and Data Warehouses at scale.
• Experience with relational databases, cloud platforms, and building secure, production-grade data pipelines.
• Strong ownership, problem-solving and communication skills.
• This role will need to secure a clearance, due to the sensitivity of the project.

EA Licence No: 20S0237