Data Engineer

Location: Norfolk, VA | Job Type: Full‑Time | Clearance: Active DoD Secret | Target Salary Range: $145,000 – $165,000

About the role

The Data Engineer designs, builds, integrates, and sustains secure enterprise data solutions that enable reliable analytics, reporting, operational insight, and informed decision‑making. The role 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. Collaboration with business intelligence, cybersecurity, infrastructure, application, and program teams is essential to translate operational requirements into governed, supportable, and reusable data products while contributing to modernization activities in an Agile/DevOps culture.

Responsibilities

• Data Pipeline Development and Integration: 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. Integrate cloud and on‑premises data platforms while supporting secure data movement, interoperability, availability, retention, and performance across hybrid environments. Develop data‑processing solutions using SQL, Python, and other approved technologies. Apply reusable engineering patterns, source control, peer review, and documented release practices.
• Data Modeling, Quality, and Performance: Build and optimize data models, schemas, tables, views, and curated data sets that support analytics, business intelligence, operational reporting, and downstream application requirements. 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.
• Requirements, Governance, and Security: Partner with analysts, BI 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.
• Modernization, Operations, and Documentation: 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, SOPs, 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.

Requirements

• Education: B.S. degree with 4–8 years of relevant experience, or M.S. degree with 2–6 years of relevant experience in data engineering, computer science, information systems, software engineering, mathematics, or a related technical discipline. Directly related experience may substitute for a degree.
• Experience: Minimum 4 years of relevant experience, including at least 3 years of hands‑on development, operation, or support of production data pipelines, data integrations, data warehouses, data lakes, or comparable enterprise data solutions. Proficiency with SQL and at least one scripting/programming language (e.g., Python). 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 relational databases, APIs, flat files, application data, system logs, or message‑based interfaces. Experience diagnosing production data issues, analyzing logs/metrics, resolving failed jobs or performance problems, and documenting root cause and corrective actions. Working knowledge of cloud and on‑premises infrastructure concepts, authentication/authorization, network connectivity, encryption, secure file transfer, and service accounts as they relate to data engineering. Familiarity with PowerShell, Python, Ansible, and practical use of large language models and AI‑enabled tools.
• Skills: Ability to work independently and collaboratively in a high‑tempo operational environment, manage competing priorities, communicate technical information clearly, and produce complete technical documentation.
• Certifications: Must possess and maintain an IAT Level II certification that satisfies applicable DoD cybersecurity workforce requirements.
• Clearance: Active DoD Secret security clearance.
• Other Requirements: U.S. citizenship. Must be located in, or able to work onsite at, a Navy Base in San Diego, CA; the Hampton Roads, VA area; or Jacksonville, FL. After‑hours support may be required to sustain mission‑critical services.

Preferred qualifications

• Business intelligence experience, including development or support of dashboards, reports, semantic models, KPIs, and self‑service analytics solutions.
• Experience with Microsoft Power BI and DAX.
• Microsoft Certified: Azure Administrator Associate.
• Hands‑on experience with Azure data and analytics services (e.g., Azure Data Factory, Azure SQL, Azure Storage, Synapse Analytics, Databricks) or comparable cloud data platforms.
• Familiarity with Security Technical Implementation Guides, the Risk Management Framework, vulnerability management, system hardening, security controls, and related compliance frameworks.
• Experience using automation, configuration‑management, source‑control, or CI/CD tools such as Ansible, Jenkins, and Bitbucket.
• Experience designing or supporting data solutions in classified, DoD, federal government, or other highly regulated environments.
• Knowledge of modern data‑platform concepts (data lakes, lake houses, dimensional modeling, streaming/event‑driven data, distributed processing, containerized workloads).
• Experience implementing data cataloging, lineage, master/reference data, role‑based access controls, audit logging, backup/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 (e.g., Neo4j) and query languages such as Cypher; modeling entities and relationships as a property graph.
• Familiarity with knowledge graphs, ontologies, semantic data models, and controlled vocabularies.
• Experience with entity resolution, record linkage, and reconciling conflicting values across multiple authoritative sources into a single trusted record.