Design, develop, and maintain scalable data pipelines to ingest, transform, validate, and operationalize data from a variety of enterprise sources
Build and support data integration workflows across structured and unstructured data sources, including APIs, files, cloud storage, databases, and enterprise platforms
Enable analytics and reporting use cases by preparing curated datasets and supporting integration with BI and analytics tools such as Tableau, Databricks, Palantir, Power BI, Qlik, or similar platforms
Support the development of data models, transformation logic, and reusable engineering patterns that improve data access, decision support, and operational visibility
Collaborate with analysts, engineers, and stakeholders to refine requirements and deliver data products aligned to mission needs
Support testing, debugging, validation, and performance tuning of data pipelines and analytics workflows
Leverage Git-based repositories and version control best practices to manage engineering efforts
Participate in Agile development activities, including sprint planning, backlog refinement, demos, and retrospectives
Document technical designs, data flows, transformation logic, and engineering processes to support maintainability and knowledge transfer
Contribute to secure, scalable, and repeatable delivery practices across cloud and DevSecOps environments

Active DoD Secret clearance
Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or a related technical discipline and 4+ years of relevant experience; or Master’s degree in a related field and 2+ years of relevant experience
Strong experience building or supporting data pipelines, ETL/ELT workflows, and data integration solutions in enterprise environments
Hands-on experience with Python and SQL
Experience with one or more modern analytics, BI, or data platform tools such as Databricks, Palantir, Tableau, Power BI, Qlik, or similar technologies
Experience supporting reporting, analytics, dashboarding, or data visualization use cases
Familiarity with cloud-based data environments and enterprise data workflows
Familiarity with Git-based version control and collaborative development workflows
Strong problem-solving and troubleshooting skills
Excellent communication and collaboration skills, with the ability to work effectively across cross-functional teams

Senior Data Engineer – Analytics, BI Platforms

Key skills