Design and build extraction, transformation, and loading (ETL) pipelines using Microsoft Fabric (Dataflow Gen2, Notebooks, or equivalent tools)
Write optimized SQL queries and transformations for data ingestion from designated source systems
Apply data quality rules and validation logic at each pipeline stage
Implement incremental loads and manage refresh schedules for performance
Define and implement data quality checks at ingestion, transformation, and output stages
Perform ongoing data validation to ensure pipeline outputs align with business logic and source system expectations
Build and maintain data transformations using Power Query, SQL, or Python as appropriate
Optimize data structures for performance and maintainability
Troubleshoot pipeline failures and performance issues; coordinate resolution with IT/Engineering
Maintain documentation of data sources, data dictionaries, and transformation specifications

Strong SQL, ETL, and data quality skills
Advanced SQL — query optimization, window functions, performance tuning, debugging complex transformations
Proficient with Microsoft Fabric — (Dataflow Gen2, Notebooks, Lakehouse) OR equivalent ETL tools (Python, dbt, Talend, Informatica)
Strong understanding of relational database design and dimensional modeling
Power Query / M — complex data shaping, merging, error handling, and transformation logic
Python or similar scripting language — data manipulation, pipeline automation
Git/version control basics — able to collaborate on code and track changes
Data quality and testing frameworks — unit tests, assertions, validation rules
Mortgage/lending domain familiarity preferred; willingness to learn domain required

Data Engineer

Key skills