DATA ENGINEER

AMSG supports a variety of Department of Defense (DoD), Department of Veterans Affairs (VA), Department of Homeland Security (DHS), Defense Health Agency (DHA), Department of the Treasury, and Federal Trade Commission (FTC) programs with performance management services. We take pride in our great work environment and highly motivated company. Join our team of top talent in supporting the federal government!

We hire Veterans and military family members!

• Serve as the subject matter expert for data engineering and data architecture within the program.
• Design, develop, and maintain robust, scalable ETL (Extract, Transform, Load) pipelines using PySpark.
• Build and manage data solutions within Palantir Foundry, ensuring data is integrated and available for analysis.
• Develop and implement data models, data warehouses, and data storage solutions for both operational and analytical purposes.
• Experience managing CI/CD processes to include branching strategies, proposal approvals, and writing test cases to ensure data compliance with existing schema expectations.
• Create and manage data pipelines that integrate data from various sources into U.S. Army data platforms such as Vantage and Advana.
• Ensure data interoperability and quality by implementing data standards, structures, and governance rules.
• Work with structured, semi-structured, and unstructured data, to support a variety of analytical requirements.
• Collaborate with data analysts and stakeholders to understand data needs and provide the necessary infrastructure to support analytics, reporting, and visualization tools.
• Provide demonstrations on data engineering efforts to an audience of varying technical backgrounds.

• Must possess an active Secret Security Clearance.
• Proven experience as a Data Engineer or Data Architect.
• Demonstrated proficiency in building ETL pipelines using PySpark.
• Hands-on experience with Palantir Foundry.
• Experience with U.S. Army systems and data environments (e.g., Vantage - Palantir Foundry, Advana).
• Strong expertise in data modeling, designing data architectures, and defining data schemas.
• Proficiency with Python in support of data engineering pipelines using Apache Spark.
• Experience handling diverse data types, including structured, semi-structured, and unstructured data.
• Ability to communicate to stakeholders of various levels of technical proficiency and breakdown concepts of data engineering and transformation logic.
• Familiarity with Machine Learning/Artificial Intelligence concepts and their data requirements (including data structure needs).

• Possess an active Top-Secret Security Clearance.
• Experience supporting business intelligence and data visualization tools (e.g. Power BI, Qlik, Tableau).
• Experience with other data processing technologies (e.g., Hadoop, Kafka).
• General knowledge of cloud data services (AWS, Azure, etc.).

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