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 ResponsibilitiesDesign 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 systemsApply data quality rules and validation logic at each pipeline stageImplement incremental loads and manage refresh schedules for performanceEscalate to Lead for architectural decisions or complex transformation patternsDefine and implement data quality checks at ingestion, transformation, and output stagesPerform ongoing data validation to ensure pipeline outputs align with business logic and source system expectationsIdentify, document, and escalate data quality issues with root cause analysisMaintain data quality dashboards and SLA monitoringSupport UAT for new data sources or transformation logicBuild and maintain data transformations using Power Query, SQL, or Python as appropriateDevelop dimensional models and define aggregation logic aligned with analytics requirementsOptimize data structures for performance and maintainabilityDocument transformation logic, lineage, and assumptions per team standardsTroubleshoot pipeline failures and performance issues; coordinate resolution with IT/EngineeringRespond to data discrepancy reports from business users and analystsMaintain documentation of data sources, data dictionaries, and transformation specificationsSupport capacity planning and optimization of Fabric environments and pipelinesCollaborate with Lead to define semantic models and calculated metricsRequirementsAdvanced SQL query optimization, window functions, performance tuning, debugging complex transformationsProficient with Microsoft Fabric — (Dataflow Gen2, Notebooks, Lakehouse) OR equivalent ETL tools (Python, dbt, Talend, Informatica)Strong understanding of relational database design and dimensional modelingPower Query / M — complex data shaping, merging, error handling, and transformation logicPython or similar scripting language — data manipulation, pipeline automationGit/version control basics — able to collaborate on code and track changesData quality and testing frameworks — unit tests, assertions, validation rulesAbility to interpret business requirements and design efficient data solutionsData governance mindset — understands data lineage, documentation, and quality standardsProactive about identifying edge cases and potential data issuesMortgage/lending domain familiarity preferred; willingness to learn domain requiredWorks effectively within defined standards and escalates architectural questions to LeadAble to balance speed with quality; advocates for technical excellence