PySpark Data Engineer Remote / Telecommute Jobs

Location: Pentagon (Onsite)

Duration: 1+ Year Contract with Extension Potential Clearance: Active TS/SCI Preferred (Secret Clearance Considered) Background Investigation: Required

Key Responsibilities: Architect, develop, and maintain scalable data pipelines supporting enterprise data ingestion, processing, and transformation. Design and optimize ETL workflows for large, complex datasets using PySpark and SQL.Build and manage data engineering solutions within the Databricks platform. Implement performance tuning strategies to improve reliability, scalability, and efficiency of data processing workloads. Develop and maintain CI/CD pipelines to support automated testing, deployment, and monitoring. Containerize and deploy applications using modern technologies such as Docker and Kubernetes. Collaborate with software engineers, analysts, architects, and stakeholders to deliver scalable data solutions. Apply DevOps principles and best practices to streamline development and deployment processes. Support data governance, data quality, and system performance initiatives. Troubleshoot and resolve data pipeline, platform, and performance-related issues.

Required Qualifications: Active TS/SCI clearance preferred; candidates with an active Secret clearance will also be considered. Strong experience working within Databricks environments. Advanced proficiency with: PySpark, SQL, ETL development and optimization, data pipeline design and engineering, implementing CI/CD pipelines and DevOps best practices, Git version control, deploying and managing containerized applications using Docker and Kubernetes. Strong understanding of distributed data processing and enterprise-scale data architectures. Ability to optimize and tune high-volume data processing workloads. Excellent problem-solving and analytical skills.