Date Engineer

Job Title: Data Engineer

Clearance: Secret Clearance

Location: Norfolk, VA

Job Type: Full-Time

Target Salary Range*: $145,000 - $165,000

*This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary

Position Overview:

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/DevOps operating culture.

Primary Responsibilities:

• 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.

Basic Qualifications:

• Requires B.S Degree and 4–8 years of prior relevant experience or Masters with 2–6 years of prior 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 be a U.S. citizen and possess an active DoD Secret Security Clearance.
• Must possess and maintain an IAT Level II certification that satisfies applicable DoD cybersecurity workforce requirements.
• Must be located in (or able to work onsite at Navy Base as required) 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 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.

Preferred Qualifications:

• Business intelligence experience, including development or support of dashboards, reports, semantic models, key performance indicators, and self-service analytics solutions; experience with Microsoft Power BI (and associated DAX knowledge) is 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 processes, system hardening, security controls, and applicable compliance frameworks.
• Experience using 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 (e.g., Neo4j) and query languages such as Cypher; modeling entities and relationships as a property graph.
• Familiarity with knowledge graphs, ontologies, or 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.