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Data Engineer with Security Clearance

Eliassen GroupNorfolk, VA🇺🇸United StatesPosted Sep 17, 2026

Why This Role Stands Out

This on-site Data Engineer role offers a fantastic opportunity to build secure, scalable enterprise data solutions within a mission-critical environment, fostering significant career growth and valuable skills development. You'll thrive here if you're a collaborative, security-cleared professional eager to contribute to modernization in an Agile and DevOps culture, with a competitive benefits package available. Apply today to leverage your expertise and make a real impact!

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Norfolk, VA, United States
Posted
22 hours ago
Neo4jSQLETLEncryptionAgileAnsibleAzureDatabricksJenkinsPower BIPowerShellPython

Job Description

On-site in Norfolk, VA Our client seeks a Data Engineer to design, build, integrate, and sustain secure enterprise data solutions that enable reliable analytics, reporting, operational insight, and informed decision-making. The role 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 Data Engineer collaborates with business intelligence, cybersecurity, infrastructure, application, and program teams to translate operational requirements into governed, supportable, and reusable data products, while contributing to modernization in an Agile and DevOps culture. Due to federal security clearance requirements, applicant must be a United States Citizen with an active Secret clearance. Due to client requirements, applicants must be willing and able to work on a w2 basis.

For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Responsibilities
Design, develop, test, deploy, and maintain scalable ETL/ELT pipelines for structured and unstructured data from systems, applications, APIs, logs, files, and databases. Build and optimize data models, schemas, tables, views, and curated datasets for analytics, business intelligence, operational reporting, and application needs.

Develop data-processing solutions using SQL and Python with reusable patterns, source control, peer review, and documented release practices. Integrate cloud and on-premises data platforms to support secure data movement, interoperability, availability, retention, and performance across hybrid 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; perform root-cause analysis and implement corrective and preventive actions. Partner with analysts, BI developers, data owners, administrators, and stakeholders to define requirements, mappings, transformation rules, 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 with minimal disruption. Create and maintain technical documentation, including architecture diagrams, data dictionaries, lineage, interface specs, runbooks, SOPs, and troubleshooting guides. Participate in Agile planning, backlog refinement, technical reviews, demonstrations, incident response, and after-hours support when required.

Experience Requirements
Proficiency with SQL and at least one scripting or programming language such as Python for extraction, transformation, validation, automation, and troubleshooting. Experience with ETL/ELT, 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.

Working knowledge of cloud and on-premises infrastructure, authentication and authorization, network connectivity, encryption, secure file transfer, and service accounts. 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 environment, manage priorities, communicate clearly, and produce complete documentation.

Working knowledge of PowerShell, Python, and Ansible, with familiarity using large language models and AI-enabled tools. Nice to have: BI experience with dashboards, reports, semantic models, KPIs, and self-service analytics; Power BI and DAX. Nice to have: Microsoft Certified Azure Administrator Associate (AZ-104). Nice to have: Hands-on experience with Azure Data Factory, Azure SQL, Azure Storage, Synapse, Databricks, or comparable cloud platforms. Nice to have: Familiarity with STIGs, RMF, vulnerability management, system hardening, security controls, and compliance frameworks.

Nice to have: Experience with Ansible, Jenkins, Bitbucket, and CI/CD practices. Nice to have: Experience in classified, DoD, federal government, or highly regulated environments. Nice to have: Knowledge of data lakes, lake houses, dimensional modeling, streaming or event-driven data, distributed processing, or containerized workloads. Nice to have: Experience with data cataloging, lineage, master or reference data, RBAC, audit logging, backup and recovery, and disaster recovery.

Nice to have: Relevant technical certifications in Azure, data engineering, database administration, analytics, cloud architecture, or security. Nice to have: Strong customer engagement, requirements analysis, technical presentations, mentoring, and cross-functional collaboration. Nice to have: Experience with graph databases such as Neo4j, Cypher, and property graph modeling. Nice to have: Familiarity with knowledge graphs, ontologies, semantic data models, and controlled vocabularies. Nice to have: Experience with entity resolution and record linkage across multiple authoritative sources.

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