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