Archived listing. The details below describe a past opening.
Required Skills & Experience
- 7+ years of Data Engineering experience.
- Hands-on Microsoft Fabric experience with production implementations.
- Strong experience with OneLake, Lakehouse architecture, and enterprise Data Lake solutions.
- Advanced SQL and Python/PySpark expertise.
- Experience designing and implementing Medallion Architecture (Bronze/Silver/Gold).
- Experience developing scalable ETL/ELT pipelines and data transformation frameworks.
- Azure Synapse and/or Azure Data Factory experience.
- Experience with CI/CD, Azure DevOps, Git, and deployment automation.
- Excellent communication skills and ability to work directly with business stakeholders.
Nice to Have Skills & Experience
- Experience leading or participating in Microsoft Fabric migration initiatives.
- Experience optimizing Fabric performance, Spark workloads, and cost efficiency.
- Data governance, lineage, security, and monitoring experience.
- Healthcare, life sciences, or regulated industry experience.
Job Description
Our Pharma client is seeking a hands-on Microsoft Fabric Data Engineer to support a large-scale data modernization initiative focused on Patient Services. This individual will play a key role in migrating existing data assets into Microsoft Fabric and building scalable, enterprise-grade data pipelines that enable analytics, reporting, and AI-driven initiatives. The ideal candidate has recent experience working within Microsoft Fabric, strong expertise with OneLake and Data Lake architectures, and a proven track record designing modern data platforms using PySpark and Medallion Architecture principles.
Responsibilities
- Design, develop, and maintain scalable data pipelines in Microsoft Fabric.
- Build and optimize solutions using OneLake, Lakehouse, Warehouse, Data Factory, SQL, and PySpark.
- Lead data ingestion, transformation, and migration efforts into Microsoft Fabric.
- Design and implement Medallion Architecture (Bronze, Silver, Gold) data models.
- Develop reusable ingestion frameworks and incremental processing solutions.
- Optimize Spark workloads, Fabric capacity, SQL performance, and overall platform efficiency.
- Implement data quality, monitoring, reconciliation, lineage, and governance controls.
- Support CI/CD processes, automated deployments, and production operations.
- Partner closely with business stakeholders, analytics teams, and data platform teams to translate requirements into scalable data solutions.
- Troubleshoot complex production issues and ensure platform reliability and operational readiness.
payrate - $70-85