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# Azure Data Engineer

- **Company:** Fedrus Global Llc
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Data Analysis, Microsoft Azure, Continuous Integration, Extract Transform Load (ETL), DevOps, Python (Programming Language), SQL Databases, Workflow Management Systems, Data Logging, Azure Data Factory, Apache Spark, Electronic Medical Records, Microsoft Fabric, Data Pipelines
- **Published:** May 26, 2026
- **Apply:** https://www.dice.com/job-detail/84946b82-0058-466e-b21a-47980d425d44

## About the Role

* 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)

Certifications (Required / Preferred)

 * DP-700 - Fabric Data Engineer Associate (Mandatory)

Preferred

 * DP-203 (Azure Data Engineer)

 * Azure/Fabric fundamentals

Domain Expectations

 * Experience with EHR, Claims, Clinical, Imaging datasets

 * Exposure to real-time or near-real-time ingestion

 * Understanding of data quality validation in pipelines

## Description

As a Data Engineer you will build and optimize scalable data pipelines on Microsoft Fabric and Azure, enabling high-quality, trusted datasets for analytics, AI, and healthcare insights, * 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


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