Principal Data Engineer

Description

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.

Responsibilities:

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.

Requirements

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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