Principal Data Engineer

• Lead the design and ongoing evolution of a Microsoft Fabric lakehouse environment, establishing a scalable architecture across raw, refined, and curated data layers.
• Create and support robust data integration workflows that bring information together from more than 30 enterprise applications and operational platforms.
• Set technical standards for data engineering, including coding practices, solution design patterns, documentation, and review processes.
• Mentor data engineers through hands-on coaching, collaborative development, and detailed code feedback to strengthen team capability.
• Partner with data and IT leadership to align platform architecture with business priorities and future expansion needs.
• Develop high-quality data pipelines using modern tools and frameworks such as SQL, Python, Spark, and PySpark within cloud-based data ecosystems.
• Evaluate new technologies, architectural approaches, and data platform trends, then provide informed recommendations for adoption.
• Support governance and platform reliability by promoting strong lineage, quality, performance, and scalable engineering practices.
• Contribute to cross-platform interoperability initiatives, including environments that may involve Databricks, governance tooling, and enterprise data services.

• Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, Business Analytics, or a related discipline; comparable relevant experience may be considered.
• At least 10 years of progressive data engineering experience with increasing technical leadership and architectural responsibility.
• Advanced expertise with Microsoft Fabric, including lakehouse design, pipelines, dataflows, notebooks, semantic models, and related platform capabilities.
• Strong command of modern cloud data technologies such as Azure Data Factory, Azure Data Lake, Delta Lake, and enterprise-scale ETL and ELT frameworks.
• Expert-level proficiency in SQL and Python, along with practical experience building solutions with Spark or PySpark.
• Demonstrated success designing and implementing medallion-style lakehouse architectures or similar large-scale data platform models.
• Experience integrating enterprise systems such as ERP, HR, CRM, service management, or field operations tools into a centralized data environment.
• Familiarity with Databricks, Unity Catalog, Microsoft Purview, or relevant Microsoft and Azure data certifications is valued.

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