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# Cloud Data Engineer (Azure)

- **Company:** General Dynamics Information Technology
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $85,093.0 - $115,000.0
- **Contract:** Permanent contract
- **Skills:** .NET Framework, Agile Methodology, Artificial Intelligence, Microsoft Azure, Big Data, Microsoft Online Services, Clinical Data Repository, Hospital Information Systems, Cloud Database, Cloud Engineering, Information Systems, Computer Programming, Databases, Information Engineering, Extract Transform Load (ETL), Data Systems, Data Visualization, Data Warehousing, DevOps, JSON, Python (Programming Language), Patient Management Software, DataOps, Azure Data Lake, SQL Databases, Azure Data Factory, Fast Healthcare Interoperability Resources, Apache Spark, Hdinsight, Electronic Medical Records, Database Migration, Pyspark, Information Technology, Health Level Seven International, Bicep, Restful APIs, Terraform, Azure Synapse Analytics, Data Pipelines, Azure Resource Manager, Databricks
- **Published:** October 14, 2026
- **Apply:** https://www.dice.com/job-detail/346b992a-8b20-4104-bd8b-803c563aac3f

## About the Role

Cloud Engineering, Data Engineering, Microsoft Azure Cloud Services, Microsoft Cloud, 3 + years of related experience, * Technical training, certification(s), or degree and 3+ years of relevant experience, or an equivalent combination of education and experience.

 * Ability to serve as a lead big data engineer on database migration and Azure-based data pipeline initiatives.
 * Extensive experience with Azure data services, including:
 + Azure Data Lake Storage Gen2
 + Azure Synapse Analytics
 + Azure Data Factory
 + Azure Monitor
 + Spark clusters (e.g., Synapse Spark, Databricks, or HDInsight)
 * Proficiency in SQL and data modeling for enterprise-scale databases and analytics environments.
 * Strong programming skills in Python (including PySpark) and .NET for large-scale data processing and integration.
 * Experience developing Infrastructure as Code (e.g., Bicep, ARM templates, Terraform) and RESTful APIs in Azure.
 * Track record of implementing CI/CD pipelines and DevOps practices for data-oriented solutions., * Experience in healthcare data systems and clinical data workflows.
 * Advanced Power BI data visualization and semantic model development skills.
 * Experience with HL7 FHIR implementation and healthcare data standards.
 * Experience with Agile methodologies and technical team leadership or mentorship.
 * Master's degree in Computer Science, Information Systems, or a related field.

LOCATION: Remote within the US

CLEARANCE: Public Trust. Must be able to obtain a Public Trust Level 5 clearance, which requires residency in the U.S. for at least 3 of the past 5 years.

## Description

GDIT is seeking a Cloud Data Engineer (Azure) to support the Indian Health Service Four Directions Data Warehouse (IHS 4DW) project.

IHS, an agency within the Department of Health and Human Services, is the principal federal health care provider and health advocate for American Indian and Alaska Native (AI/AN) people. This role supports a mission-critical modernization effort: retiring the Resource and Patient Management System (RPMS) and moving to a new electronic health record (EHR) system.

At GDIT, people are our differentiator. As a Cloud Data Engineer, you'll help deliver cutting-edge cloud and data solutions that directly support improved healthcare outcomes while growing your career in a collaborative, mission-driven environment.

HOW YOU WILL MAKE AN IMPACT

 * Lead the modernization of IHS health records by establishing a central repository for clinical data and longitudinal patient records.
 * Design and implement Azure data pipelines to consolidate clinical data from 200+ healthcare facilities into an enterprise analytics environment.
 * Develop automated ETL processes for high-volume JSON/HL7 FHIR data using Azure Data Factory and Azure Data Lake.
 * Create and optimize PySpark processes for large-scale healthcare data transformation and enrichment.
 * Build and maintain enterprise data models to standardize clinical information across facilities and data sources.
 * Implement monitoring and alerting solutions to ensure data quality, reliability, and pipeline performance.
 * Collaborate with architects, data engineers, and stakeholders to define cloud data architecture and integration patterns.
 * Provide technical leadership on Azure cloud and data engineering best practices.