Apetan Consulting is seeking a Data Engineer to support a Healthcare AI initiative using Microsoft Fabric and Azure. The role involves designing and maintaining data pipelines for healthcare datasets to facilitate AI/ML projects.
Job Title: Data Engineer (Microsoft Fabric | Healthcare AI Initiative) Location: Houston, TX (Client HQ) Duration: Contract to Hire (Conversion required, no sponsorship available) Job Description: We are seeking a Data Engineer to support a Healthcare AI initiative leveraging Microsoft Fabric and modern data engineering tools. The ideal candidate will have strong experience with data ingestion, orchestration, and transformation in cloud-based environments, particularly Azure. Responsibilities: • Design, develop, and maintain scalable data pipelines within Microsoft Fabric and Azure ecosystem. • Work with structured and unstructured healthcare datasets to support AI/ML initiatives. • Build and optimize data ingestion, processing, and storage solutions using Spark, Delta tables, SQL Server, and Python. • Collaborate with data scientists, analysts, and product teams to deliver clean, reliable, and accessible datasets. • Ensure compliance with healthcare data standards and governance best practices. Required Skills: • Strong hands-on experience with Microsoft Fabric and Azure Data Services. • Expertise in Spark, Python, SQL Server, and Delta tables. • Proven track record of building and orchestrating data ingestion pipelines. • Prior experience in healthcare data (claims, EHR, patient, or related). • Strong understanding of data governance, compliance, and security in healthcare contexts. • Familiarity with AI/ML pipelines and integration with healthcare analytics. • Experience working in large-scale enterprise environments. • Strong communication skills to work with cross-functional teams. Additional Information: Must be able to convert to full-time without sponsorship
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Apetan Consulting is seeking a Data Engineer to support a Healthcare AI initiative using Microsoft Fabric and Azure. The role involves designing and maintaining data pipelines for healthcare datasets to facilitate AI/ML projects.