Trace3
W2PE - Engineer
About this role
Trace3 seeks a Fabric Data Engineer to design and build scalable, metadata-driven ETL pipelines in Microsoft Fabric as part of an enterprise data modernization initiative. You'll implement medallion architecture (Bronze, Silver, Gold) using Python and parameterized notebooks, modernize legacy pipelines, and transfer knowledge to the internal data engineering team.
What you'll do
- Design and build metadata-driven, reusable data pipelines in Microsoft Fabric across multiple source systems
- Develop and maintain Bronze, Silver, and Gold layers in Fabric Lakehouse/Warehouse with validation and quality gates
- Create Python and PySpark notebooks for scalable, parallel data processing with incremental and restartable logic
- Implement data quality checks and validation controls at each pipeline layer with operational evidence and auditability
- Partner with data governance and analytics teams to align pipeline design with organizational standards
- Document architecture, code, and runbooks while actively transferring operating knowledge to the data engineering team
What they're looking for
- Python and PySpark for data pipeline development
- Microsoft Fabric (notebooks, Lakehouse, Warehouse, orchestration)
- Metadata-driven and parameterized pipeline design patterns
- Medallion architecture (Bronze, Silver, Gold layers)
- ETL/ELT pipeline design and optimization
- Data quality, validation, and testing frameworks
- SQL for data transformation and warehouse operations
- Cloud data platform experience (Databricks or equivalent)
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Trace3
Trace3 builds and optimizes complex defense and military systems, including battle management platforms, sensor resource management solutions, and enterprise system architectures for DoD programs. The company is hiring Systems Engineers, Performance Assessment Engineers, Software Engineers, and Test Engineers to design, develop, analyze, and validate these critical defense systems.
- Website
- trace3.com
Likely interview questions
- Walk us through a metadata-driven pipeline you've built—how did parameterization reduce maintenance overhead compared to one-off pipelines?
- Describe your experience implementing medallion architecture. How did you ensure data quality gates between Bronze, Silver, and Gold layers?