Parsons Corporation

Data Engineer

Rol remoto de Data Engineering con fit claro de ubicación del candidato.

Publicado19 jul 2026

Países elegibles1 país aceptado

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

Estados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

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.

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.

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