Senior Data Engineer
breezy
Job Description
- Design and own the canonical data model — co-create the normalised ERD (3NF) with Solutions and Product, defining naming conventions, data types, and relationship standards that all deployments conform to
- Build the medallion data platform (Bronze → Silver → Gold) on AWS using S3, DMS, Glue, Redshift Serverless, and QuickSight — from CDC ingestion through to self-serve dashboards
- Develop and maintain CDC pipelines and ETL jobs that ingest data from Amazon RDS, apply business logic, calculate KPIs, and produce clean, analytics-ready star schemas
- Migrate client schemas to the standard model, starting with a pilot account and scaling across all accounts with row-level tenant isolation. Each client deployment carries its own schema customisations and configuration variations; a core challenge of this role is normalising divergent client data models into the canonical ERD without losing client-specific fidelity
- Enable self-serve BI for Customer Success — build the Gold-layer flat marts and analytics-ready schemas that enable self-serve QuickSight dashboards, so the CS team can generate QBR materials in under two days without specialist involvement
- Establish data governance processes including change control for schema modifications, a data dictionary, cataloging standards via Glue Data Catalog, and audit-ready data lineage
- Lay the data foundation for AI/ML — ensure clean, historical data pipelines that support future AI use cases, and cross-client benchmarking models
- Collaborate cross-functionally with Product Engineering on schema migration, Solutions on ERD validation and regression testing, and the AI team on model training data requirements