Data Engineer (w/ active Secret)

Critical Solutions•Norfolk, VA

1d•$87,000 - $112,000•Onsite

About The Position

Critical Solutions is seeking a Data Engineer to support a federal customer. The role designs, builds, integrates, and sustains secure enterprise data solutions that enable analytics, reporting, operational insight, and decision-making. It develops scalable data pipelines, integrates diverse data sources, improves data quality and availability, and supports cloud and on-premises platforms in a mission-critical environment. The engineer works with business intelligence, cybersecurity, infrastructure, application, and program teams to turn operational requirements into governed, supportable, reusable data products, contributing to modernization in an Agile/DevOps environment. The position is onsite 100% in Norfolk, Virginia, with San Diego, California, and Jacksonville, Florida also listed as acceptable work locations. The candidate must be a U.S. citizen and have an active DoD Secret clearance or higher; the selected candidate must also complete the federal agency’s background investigation and fingerprinting. A maintained IAT Level II certification satisfying applicable DoD cybersecurity workforce requirements is required. The position requires a bachelor’s degree with relevant experience and at least four years of relevant experience, although additional directly related experience may be considered in place of a degree. The posting also requires at least three years of hands-on production data engineering experience. The stated salary range is $87,000–$112,000, subject to location and other factors. Benefits include 100% premium coverage for medical, dental, vision, and life insurance; supplemental insurance; 401(k) matching; flexible time off and holidays; and higher education and training reimbursement.

Requirements

U.S. citizenship and an active DoD Secret Security Clearance or higher.
A bachelor’s degree 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.
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.
Must possess and maintain an IAT Level II certification that satisfies applicable DoD cybersecurity workforce requirements.
Must be located in San Diego, California; the Hampton Roads, Virginia area; or Jacksonville, Florida.
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 infrastructure concepts, authentication and authorization, network connectivity, encryption, secure file transfer, and service accounts as they relate to data engineering.
Experience diagnosing production data issues, analyzing logs and metrics, resolving failed jobs or performance problems, and documenting root cause and corrective action.
Ability to work independently and collaboratively in a high-tempo operational environment, manage competing priorities, communicate technical information clearly, and produce complete technical documentation.
Working knowledge of PowerShell, Python, and Ansible, with practical familiarity using large language models (LLMs) and AI-enabled tools.

Nice To Haves

Business intelligence experience, including developing or supporting dashboards, reports, semantic models, key performance indicators, and self-service analytics; Microsoft Power BI and associated DAX knowledge are highly desirable.
Microsoft Certified: Azure Administrator Associate (AZ-104) certification.
Hands-on experience with Azure data and analytics services such as Azure Data Factory, Azure SQL, Azure Storage, Synapse Analytics, Databricks, or comparable cloud data platforms.
Familiarity with Security Technical Implementation Guides (STIGs), the Risk Management Framework (RMF), vulnerability management, system hardening, security controls, and applicable compliance frameworks.
Experience with automation, configuration-management, source-control, or continuous integration and delivery tools such as Ansible, Jenkins, and Bitbucket.
Experience designing or supporting data solutions in classified, DoD, federal government, or other highly regulated environments.
Experience with modern data-platform concepts and technologies, including data lakes, lake houses, dimensional modeling, streaming or event-driven data, distributed processing, or containerized workloads.
Experience implementing data cataloging, lineage, master or reference data, role-based access controls, audit logging, backup and recovery, and disaster-recovery practices.
Relevant technical certifications in Azure, data engineering, database administration, analytics, cloud architecture, or security.
Strong customer engagement, requirements analysis, technical presentation, mentoring, and cross-functional collaboration skills.
Experience with graph databases such as Neo4j and query languages such as Cypher, including modeling entities and relationships as a property graph.
Familiarity with knowledge graphs, ontologies, semantic data models, or controlled vocabularies.
Experience with entity resolution or record linkage and reconciling conflicting values across multiple authoritative sources into a single trusted record.

Responsibilities

Design, develop, test, deploy, and maintain scalable ETL/ELT pipelines for 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 for analytics, business intelligence, operational reporting, and downstream applications.
Develop data-processing solutions using SQL, Python, and other approved technologies, applying reusable engineering patterns, source control, peer review, and documented release practices.
Integrate cloud and on-premises data platforms and support secure data movement, interoperability, availability, retention, and performance in hybrid enterprise environments.
Implement automated data-quality checks, reconciliation controls, monitoring, alerting, and exception handling.
Troubleshoot pipeline failures, data discrepancies, performance degradation, access issues, and integration defects; conduct root-cause analysis and implement corrective and preventive actions.
Work with analysts, business intelligence developers, data owners, system administrators, and mission stakeholders to define requirements, mappings, transformation rules, service expectations, and acceptance criteria.
Apply data governance, security, privacy, least-privilege access, auditability, and records-retention requirements 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, and incident response; provide after-hours support when required to sustain mission-critical services.