W2PE - Engineer

Who is Trace3 ? Trace3 is a leading Transformative IT Authority, providing unique technology solutions and consulting services to our clients. Equipped with elite engineering and dynamic innovation, we empower IT executives and their organizations to achieve competitive advantage through a process of Integrate, Automate, Innovate. Our culture at Trace3 embodies the spirit of a startup with the advantage of a scalable business. Employees can grow their career and have fun while doing it! Trace3 is headquartered in Irvine, California. We employ more than 1,200 people all over the United States. Our major field office locations include Denver, Indianapolis, Grand Rapids, Lexington, Los Angeles, Louisville, Texas, San Francisco.   Ready to discover the possibilities that live in technology? Come Join Us! Street-Smart   -  Thriving in Dynamic Times We are flexible and resilient in a fast-changing environment. We continuously innovate and drive constructive change while keeping a focus on the “big picture.” We exercise sound business judgment in making high-quality decisions in a timely and cost-effective manner. We are highly creative and can dig deep within ourselves to find positive solutions to different problems. Juice -  The “Stuff” it takes to be a Needle Mover We get things done and drive results. We lead without a title, empowering others through a can-do attitude. We look forward to the goal, mentally mapping out every checkpoint on the pathway to success, and visualizing what the final destination looks and feels like. Teamwork -  Humble, Hungry and Smart We are humble individuals who understand how our job impacts the company's mission. We treat others with respect, admit mistakes, give credit where it’s due and demonstrate transparency. We “bring the weather” by exhibiting positive leadership and solution-focused thinking. We hug people in their trials, struggles, and failures – not just their success. We appreciate the individuality of the people around us. JOB SUMMARY Trace3 is seeking a Fabric Data Engineer to accelerate the enterprise Data Modernization program by building and refactoring scalable, metadata-driven ETL pipelines in Microsoft Fabric. This role will design and implement medallion architecture (Bronze, Silver, Gold) using parameterized Python notebooks to move source data from landing through governed, trusted analytical layers, reducing dependence on legacy ETL platforms and enabling faster, more reliable speed-to-insight for enterprise reporting. The Fabric Data Engineer will work hands-on to modernize existing pipelines, apply reusable and parallelized data-processing patterns, and support the broader Fabric medallion implementation already underway as part of Phase 1C of the program. This is a delivery-focused engineering role with an explicit expectation of transferring architecture, code, and operating knowledge to the current data-engineering team as the program matures. SUMMARY OF ESSENTIAL JOB FUNCTIONS Fabric Pipeline & Metadata-Driven Engineering Design, build, and maintain metadata-driven data pipelines in Microsoft Fabric that are reusable across source systems and entities rather than built one-off per pipeline. Develop and maintain a metadata/configuration-driven framework that governs ingestion, transformation, and load behavior across the pipeline estate. Standardize ingestion patterns using parameterized notebooks to minimize duplicate logic and simplify ongoing maintenance. Medallion Architecture Implementation Build and refactor Bronze, Silver, and Gold layers in the Fabric Lakehouse/Warehouse, ensuring each layer meets defined validation and quality gates before promotion. Preserve source fidelity in the landing zone and implement conformed, deduplicated, and historized data in Silver in support of downstream Gold transformations. Apply warehouse-side transformation logic and support native-service patterns (e.g., Dataflows Gen2, Fabric Data Factory) as part of the broader platform modernization effort. Python Notebook Development & Parallel Processing Develop Python notebooks (including PySpark-based processing) to support scalable, parallel data-processing pipelines that improve data-processing efficiency and reduce time to insight. Build restartable, incremental, and schema-aware processing logic that scales across growing data volumes and source counts. Data Quality, Validation & Operational Controls Implement data validation and quality checks at each layer (landing, Bronze, Silver, Gold) rather than treating validation as an end-stage activity. Maintain operational evidence for pipeline runs, notebook executions, merges, and quality results to support troubleshooting and auditability. Support performance tuning, refresh-frequency optimization, and capacity-efficient pipeline design within Fabric. Collaboration, Documentation & Knowledge Transfer Partner with the Director, Data and Analytics Enablement and the current data-engineering team to align pipeline design with governance, metadata, and certified-dataset standards. Document architecture, code, and runbooks, and actively transfer operating knowledge so the current data-engineering team can independently operate, troubleshoot, and extend delivered pipelines. Collaborate with reporting, governance, and platform stakeholders to ensure pipeline outputs support trusted, consistent enterprise reporting. REQUIRED SKILLS AND EXPERIENCE 3+ years of hands-on data engineering experience building production ETL/ELT pipelines. Demonstrated experience designing and implementing metadata-driven data pipelines (parameterized, configuration-based pipeline patterns rather than one-off builds). Strong proficiency in Python, including experience building notebook-based data-processing pipelines (PySpark or equivalent) for parallel/distributed processing. Hands-on experience with Microsoft Fabric and/or Databricks, i