<p>We are looking for a Principal Data Engineer to shape and lead a modern enterprise data platform serving multiple business lines. This position will define the architectural direction for a Microsoft Fabric-based environment, guide engineering best practices, and partner closely with data and IT leaders to support long-term growth. The role is ideal for a senior technical expert who combines deep hands-on engineering capability with strong mentorship and platform strategy experience.</p><p><br></p><p>Responsibilities:</p><p>• Lead the design and ongoing evolution of a Microsoft Fabric lakehouse environment, establishing a scalable architecture across raw, refined, and curated data layers.</p><p>• Create and support robust data integration workflows that bring information together from more than 30 enterprise applications and operational platforms.</p><p>• Set technical standards for data engineering, including coding practices, solution design patterns, documentation, and review processes.</p><p>• Mentor data engineers through hands-on coaching, collaborative development, and detailed code feedback to strengthen team capability.</p><p>• Partner with data and IT leadership to align platform architecture with business priorities and future expansion needs.</p><p>• Develop high-quality data pipelines using modern tools and frameworks such as SQL, Python, Spark, and PySpark within cloud-based data ecosystems.</p><p>• Evaluate new technologies, architectural approaches, and data platform trends, then provide informed recommendations for adoption.</p><p>• Support governance and platform reliability by promoting strong lineage, quality, performance, and scalable engineering practices.</p><p>• Contribute to cross-platform interoperability initiatives, including environments that may involve Databricks, governance tooling, and enterprise data services.</p>

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

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