Data Engineer

Parsons Corporation is seeking a talented Data Engineer to join their team. The role involves designing and maintaining scalable data pipelines, optimizing data architecture, and collaborating with cross-functional teams to support advanced analytics and data management efforts.

Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL processes to ingest, transform, and enrich large volumes of chemical and biological threat data from diverse sources
• Implement and optimize data architecture to support data quality, validation, and enrichment workflows
• Integrate data from existing data lakes and external systems via APIs, ensuring interoperability and data consistency across the enterprise
• Develop and maintain robust metadata management and data catalog systems to facilitate data discovery, lineage tracking, and governance
• Collaborate with software developers, AI/ML engineers, and stakeholders to support advanced analytics, predictive modeling, and knowledge graph construction
• Implement data partitioning, classification, and access control strategies to comply with NIST SP 800-171 and DoD security requirements
• Automate data quality assessments, error detection, and remediation processes; generate data quality reports and support continuous improvement
• Support the integration of legacy data, resolving inconsistencies and standardizing formats to align with current data standards and ontologies
• Participate in Agile sprints, backlog refinement, and sprint reviews; contribute to technical documentation and data management plans
• Assist in knowledge transfer and training activities, including the development of user guides and best practices for data management

Requirements:

• Active Secret or higher security clearance
• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field
• 3-8 years of experience in data engineering, data integration, or ETL development in cloud or enterprise environments
• Proficiency with data engineering tools and languages (e.g., SQL, Python, Spark, or similar)
• Experience building and managing scalable data pipelines and ETL workflows
• Hands-on experience with cloud platforms (e.g., AWS, Azure, or similar) and cloud-native data services
• Strong understanding of data modeling, data partitioning, and data architecture best practices
• Experience with metadata management, data cataloging, and data governance frameworks
• Familiarity with data security, encryption, and access control mechanisms
• Experience working in Agile development environments and collaborating with cross-functional teams
• Strong analytical, problem-solving, and communication skills
• Master's degree in Data Engineering, Computer Science, or a related field
• Experience implementing data architectures and federated data access models
• Familiarity with DoD cybersecurity and data governance standards (e.g., NIST SP 800-171, STIG, RMF)
• Experience with data quality assessment tools and automated data validation frameworks
• Experience integrating data from classified environments (e.g., SIPR, JWICS)
• Knowledge of advanced search and indexing technologies (e.g., vector/semantic search, LLMs)
• Knowledge of modern database platforms (e.g. Postgres (preferred), MongoDb, MySQL, Neo4j)
• Experience with containerization (Docker, Kubernetes) and container security best practices
• Experience developing and maintaining knowledge graphs and ontologies
• Prior experience supporting government or defense-related data projects