Key skills
PythonSQLSparkAzure Data ServicesMicrosoft FabricETL pipelinesELT pipelinesData modelingSchema designAirflowFabric Data FactorySpark notebooksLakehouseMedallion architectureOneLakeAzure ecosystemEvent StreamsEvent HubDP-700 Fabric Data Engineer AssociateDP-203 Azure Data EngineerAzure fundamentalsEHR datasetsClaims datasetsClinical datasetsImaging datasetsData quality validationCI/CDDevOpsAIETLELTAnalyticsAzure
About this role
Dice is seeking an Azure Data Engineer to build and optimize scalable data pipelines on Microsoft Fabric and Azure. The role involves enabling high-quality, trusted datasets for analytics, AI, and healthcare insights.
Responsibilities:
- Develop batch and real-time pipelines using Fabric, Azure, Python, and Spark
- Build standardized ingestion frameworks for healthcare data sources
- Implement data transformations and Medallion architecture layers
- Embed data quality validations within pipelines
- Ensure data performance, scalability, and cost efficiency
- Implement monitoring, logging, and observability frameworks
- Support CI/CD, orchestration, and DevOps processes
- Collaborate on data modeling, lineage, and mappings
Requirements:
- Strong expertise in Python, SQL, Spark (5+ years)
- Hands-on experience with Azure Data Services & Microsoft Fabric
- Experience building ETL/ELT pipelines and ingestion frameworks
- Strong data modeling and schema design skills
- Experience with workflow orchestration tools (Airflow/Fabric pipelines)
- Microsoft Fabric Expertise
- Fabric Data Factory (pipelines), Spark notebooks, Lakehouse
- Experience implementing Medallion architecture within Fabric
- Integration with OneLake and Azure ecosystem
- Exposure to real-time ingestion (Event Streams/Event Hub)
- DP-700 – Fabric Data Engineer Associate (Mandatory)
- DP-203 (Azure Data Engineer)
- Azure/Fabric fundamentals
- Experience with EHR, Claims, Clinical, Imaging datasets
- Exposure to real-time or near-real-time ingestion
- Understanding of data quality validation in pipelines