Data Engineer

About the Company We are looking for a new Data Engineer to be part of the Mortgage Cadence team.

The Data Engineer operates designing, building and maintaining robust data pipelines and transformation logic that powers 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.

RESPONSIBILITIES Data Pipeline Development: • Design and build 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

Data Quality & Validation: • 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

Transformation & Modeling: • 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 • Collaborate with Lead to define semantic

Operational Support: • 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 models and calculated metrics