Senior Data Engineer with strong Microsoft Fabric
ESRhealthcare and EXEC STAFF RECRUITERS
Job Description
Job Description
Mesa/Phoenix, AZ area, is seeking a Mid-Level to Senior Data Engineer with strong Microsoft Fabric expertise. This is a direct hire opportunity working closely with the hiring manager. The company offers a competitive compensation package and a hybrid work model (must reside in the Phoenix metro area). Position Overview: This role focuses on designing, building, and optimizing scalable data pipelines and platform components within Microsoft Fabric. The Data Engineer will play a key role in enabling analytics and machine learning initiatives, ensuring data is high-quality, governed, and performant while collaborating across IT and business teams. Responsibilities:
- Design and manage Fabric Lakehouse architectures (OneLake, medallion patterns)
- Build and orchestrate ETL/ELT pipelines using Data Factory, Spark, and SQL
- Optimize and administer Fabric workloads, capacity, and performance
- Support delivery of ML-ready datasets, feature stores, and inference pipelines
- Implement CI/CD pipelines and support model deployment lifecycle (MLOps)
- Establish data quality, lineage, governance, and monitoring standards
- Optimize Spark/SQL performance for scalability and cost efficiency
- Collaborate cross-functionally and contribute to best practices and reusable assets
- Bachelor's or Masters degree in Computer Science, Information Systems, Data Engineering or related field
- At least 3-5+ years of Data Engineering experience
- Strong hands-on experience with Python and SQL
- Proven experience with Microsoft Fabric (Lakehouse, OneLake, Data Factory, Spark) and Power BI integration
- Experience with modern data formats (Delta Lake, Parquet, Spark)
- Familiarity with data governance (Purview, RBAC)
- Experience with CI/CD, Git, and automated testing for data platforms
Preferred Qualifications:
- Experience integrating Fabric with Azure services (ADLS, Azure SQL/MI, Event Hubs, Synapse)
- Exposure to MLOps practices (feature stores, model registry, monitoring)
- Knowledge of Power BI semantic models, Direct Lake/DirectQuery
- Experience with streaming or near real-time data architectures
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