Senior Data Engineer Databricks
Our client is a global financial services organisation that uses data at scale to support critical business decisions worldwide. The data team works mainly on a central Databricks platform, building reliable and high-quality data solutions used across the business.
This role is for a strong data engineer who enjoys working deep in Databricks, understands Spark well, and has solid engineering fundamentals. It is not a pure cloud engineering role. The main focus is building, improving, and optimising data pipelines on Databricks.
What you will do
Build and maintain data pipelines using Databricks and Spark
Work on batch and streaming data processing
Optimise Spark jobs and Databricks clusters for performance and reliability
Use Delta Lake and Lakehouse patterns for clean and trusted data
Apply good engineering practices around testing, version control, and documentation
Work closely with other data engineers, analysts, and technical teams
Contribute to code reviews and technical improvements
Must have
Strong experience as a data engineer
Hands-on experience with Databricks
Good knowledge of Spark and Python
Experience building and optimising ETL or ELT pipelines
Solid SQL and data modelling skills
Cloud experience with AWS or similar
Strong engineering fundamentals and problem-solving skills
Comfort working in an agile engineering team
Nice to have
Experience in financial services
Experience with streaming data
API integration experience
Interest or experience using AI tools in development
If you enjoy Databricks, Spark, and building solid data solutions, this role is a great next step.