Senior Data Engineer – AWS, Databricks & Spark

About the role

Join a leading financial services organisation on a major data platform transformation programme. As a Senior Data Engineer you will design, build and operationalise an enterprise‑grade data platform that serves risk, treasury, finance and regulatory teams.

Key responsibilities

• Design and develop scalable data solutions in AWS and Databricks.
• Build batch, near‑real‑time and real‑time pipelines ingesting structured and unstructured sources.
• Transform, normalise, enrich and aggregate large datasets using Apache Spark or PySpark.
• Implement lakehouse and medallion architectures, canonical data models and data quality controls.
• Create automated deployment pipelines with CI/CD, DevOps or GitOps practices.
• Optimise pipelines for performance, reliability and cost.
• Produce technical documentation, runbooks and support procedures.
• Collaborate with architects, analysts, product owners and stakeholders in Agile ceremonies.

Required profile

• Senior‑level, hands‑on engineering experience.
• Proven track record delivering enterprise‑scale data platforms in the financial sector.
• Strong problem‑solving skills and ability to take solutions from design to production.

Required skills

• AWS
• Databricks
• Apache Spark
• PySpark
• CI/CD
• GitOps / DevOps practices
• Lakehouse architecture
• Data quality, lineage and governance controls

What we offer

• Hybrid working model.
• Fixed‑term contract until 31 December 2026.
• Opportunity to work on high‑impact financial data products.