Data Engineer; w​/active Secret

Critical Solutions is seeking a Data Engineer to support our federal customer.

Location:

Norfolk, VA

Clearance:
Secret

Type:
Full-time, Onsite

Salary Range: $87,000 - $112,000

The Data Engineer designs, builds, integrates, and sustains secure enterprise data solutions that enable reliable analytics, reporting, operational insight, and informed decision-making. The position develops scalable data pipelines, integrates data from diverse sources, improves data quality and availability, and supports cloud and on-premises platforms in a mission-critical environment. The Data Engineer works closely with business intelligence, cybersecurity, infrastructure, application, and program teams to translate operational requirements into governed, supportable, and reusable data products;

and will contribute to modernization activities in an Agile/Dev Ops operating culture.

• Design, develop, test, deploy, and maintain scalable ETL/ELT pipelines that collect, transform, validate, and deliver structured and unstructured data from enterprise systems, applications, APIs, logs, files, and databases.
• Build and optimize data models, schemas, tables, views, and curated data sets that support analytics, business intelligence, operational reporting, and downstream application requirements.
• Develop data-processing solutions using SQL, Python, and other approved technologies; apply reusable engineering patterns, source control, peer review, and documented release practices.
• Integrate cloud and on-premises data platforms while supporting secure data movement, interoperability, availability, retention, and performance across hybrid enterprise environments.
• Implement automated data-quality checks, reconciliation controls, monitoring, alerting, and exception handling to identify incomplete, inaccurate, duplicated, delayed, or failed data flows.
• Troubleshoot pipeline failures, data discrepancies, performance degradation, access issues, and integration defects; perform root cause analysis and implement corrective and preventive actions.
• Partner with analysts, business intelligence developers, data owners, system administrators, and mission stakeholders to define data requirements, source-to-target mappings, transformation rules, service expectations, and acceptance criteria.
• Apply data governance, security, privacy, least-privilege access, auditability, and records-retention requirements throughout the data lifecycle in coordination with cybersecurity and compliance teams.
• Support platform upgrades, data migrations, modernization initiatives, capacity planning, and performance tuning while minimizing disruption to production services.
• Create and maintain technical documentation, including architecture diagrams, data dictionaries, lineage documentation, interface specifications, runbooks, standard operating procedures, and troubleshooting guides.
• Participate in Agile planning, backlog refinement, technical reviews, demonstrations, incident response, and after-hours support activities when required to sustain mission-critical services.

• Must be a U.S. citizen and possess an active DoD Secret Security Clearance or higher.
• Minimum B.S Degree with relevant experience in data engineering, computer science, information systems, software engineering, mathematics, or a related technical discipline, with at least four years of relevant experience; additional directly related experience may be considered in place of a degree.
• Must possess and maintain an IAT Level II certification that satisfies applicable DoD cybersecurity workforce requirements.
• Must be located in either San Diego, California; the Hampton Roads, Virginia area or Jacksonville, FL.
• At least three years of hands-on experience developing, operating, or supporting production data pipelines, data integrations, data warehouses, data lakes, or comparable enterprise data solutions.
• Demonstrated proficiency with SQL and at least one general-purpose scripting or programming language, such as Python, for data extraction, transformation, validation, automation, and troubleshooting.
• Experience with ETL/ELT concepts, relational data structures, data modeling, schema design, source-to-target mapping, data quality, metadata, and lifecycle management.
• Experience integrating data from multiple source types, including relational databases, APIs, flat files, application data, system logs, or message-based interfaces.
• Working knowledge of cloud and on-premises…