Job description
The Data Engineer operates within the framework established by the Lead — designing, building, and maintaining robust data pipelines and transformation logic that power analytics, compliance, and operational reporting across the Mortgage Cadence Platform.
The role is execution-focused with increasing ownership of end-to-end data workflows as familiarity with the platform grows.
Strong SQL, ETL, and data quality skills are required; the ability to build reports and leverage semantic models is secondary to data engineering excellence.
Job Responsibilities 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 Escalate to Lead for architectural decisions or complex transformation patterns 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 Identify, document, and escalate data quality issues with root cause analysis Maintain data quality dashboards and SLA monitoring Support UAT for new data sources or transformation logic Build and maintain data transformations using Power Query, SQL, or Python as appropriate Develop dimensional models and define aggregation logic aligned with analytics requirements Optimize data structures for performance and maintainability Document transformation logic, lineage, and assumptions per team standards Troubleshoot pipeline failures and performance issues; coordinate resolution with IT/Engineering Respond to data discrepancy reports from business users and analysts Maintain documentation of data sources, data dictionaries, and transformation specifications Support capacity planning and optimization of Fabric environments and pipelines Collaborate with Lead to define semantic models and calculated metrics 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 Ability to interpret business requirements and design efficient data solutions Data governance mindset — understands data lineage, documentation, and quality standards Proactive about identifying edge cases and potential data issues Mortgage/lending domain familiarity preferred; willingness to learn domain required Works effectively within defined standards and escalates architectural questions to Lead Able to balance speed with quality; advocates for technical excellence
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