Junior Data Engineer

Brown & Brown is seeking a Junior Data Engineer to join our growing team! This role will support ingestion, transformation, modeling, and delivery of complex healthcare datasets including medical and pharmacy claims, eligibility, provider, and clinical data.

Responsibilities:

• Design and implement end-to-end data pipelines within Azure Synapse Analytics, including:
• Synapse Pipelines
• Dedicated and serverless SQL pools
• Synapse Spark for distributed processing
• Build scalable ELT workflows transforming raw healthcare data into analytics-ready structures
• Optimize distributed workloads for performance and cost efficiency
• Design layered architecture using Azure Data Lake Storage and Synapse
• Develop healthcare data models across claims, eligibility, provider, and service dimensions
• Build aggregated datasets (PMPM, utilization, risk scoring, provider performance)
• Performance optimization/troubleshooting of existing data and pipelines
• Clear/concise documentation of data transformations and key data details

Requirements:

• Bachelor's degree in Computer Science, Data Engineering, or related field
• 0-3 years of data engineering experience (healthcare strongly preferred)
• Strong SQL expertise and proficiency in Python or PySpark
• Hands-on experience with Azure Synapse Analytics (SQL pools, Spark, pipelines)
• Hands-on experience with Azure Data Lake Storage
• Experience building scalable ELT pipelines and dimensional data models
• Familiarity with healthcare datasets (claims, eligibility, provider data)
• Azure Certification Requirement (one or more of the following): Microsoft Certified: Azure Data Engineer Associate (DP-203) or equivalent, Microsoft Certified: Azure Fundamentals (AZ-900) (minimum baseline expected)
• Experience designing enterprise data warehouses within Synapse
• Familiarity with lakehouse architectures (Delta Lake, Spark)
• Experience with CI/CD (Azure DevOps, GitHub Actions)
• Exposure to value-based care or population health analytics