Senior Data Engineer

• Help redefine the platform’s architecture across ingestion, processing and delivery, so it’s stable, secure and fast enough to support advanced use cases for the business.

• Build and operate batch and streaming pipelines from databases, APIs, event streams and semi-structured sources.

• Implement change data capture and incremental load, including ordering, deletes, replay and slowly changing dimensions.

• Build medallion datasets and dimensional models, and deliver them to Snowflake, Microsoft SQL Server and Databricks.

• Apply data contracts, reconciliation and row-level quarantine before publication.

• Own the GitHub workflow and CI/CD, including tests, review, environment promotion and deployment as code.

• Investigate production data failures, and turn requirements from product, valuation and client-facing teams into operable pipelines.

Requirements

• 10+ years in data engineering on production systems.

• Snowflake or Databricks as a primary platform, including modelling, performance tuning and cost management.

• Python and SQL for pipeline development and testing.

• Change data capture and event processing, including ordering, replay and schema change.

• Azure, including Databricks, ADLS and private network connectivity.

• GitHub and CI/CD for data workloads, using GitHub Actions or an equivalent system.

• Data quality, reconciliation, monitoring and production incident response.

• Experience building multi-tenant, secure data platforms, including tenant isolation, access control and data protection.