Data Engineer

Amatriot Group, LLC; Norfolk (VA); On-site; USD 145,000 - 165,000; Full time

Job summary

Amatriot Group, LLC is seeking a Data Engineer to design, build, integrate, and sustain secure enterprise data solutions in a mission-critical environment. You will develop scalable data pipelines, integrate diverse data sources, and support cloud and on-premises platforms while collaborating with BI, cybersecurity, and infrastructure teams.

Required: 4+ years in data engineering, strong SQL and Python skills, experience with ETL/ELT, data modeling, and data quality.

Qualifications

• At least 4 years of relevant data engineering experience.
• 3+ years building, operating, or supporting production data pipelines.
• Proficiency in SQL and Python for data extraction, transformation, and validation.
• Experience with ETL/ELT concepts, data modeling, and data quality.
• Experience with cloud and on-premises data platforms; DoD environment familiarity.

Responsibilities

• Design, develop, test, deploy, and maintain scalable ETL/ELT pipelines.
• Integrate cloud and on-premises data platforms for secure data movement.
• Build data models, schemas, views, and curated data sets for analytics.
• Implement automated data quality checks, monitoring, and reconciliations.
• Collaborate with BI, cybersecurity, and program teams in an Agile/DevOps culture.
• Create technical documentation and runbooks; support incident response.

Skills

SQL

Python

ETL/ELT

Data modeling

Data quality

Cloud & on-prem

Agile/DevOps

Communication

Education

B.S. in Data Engineering or related field

Master's in related field

Experience may substitute for degree

Tools

PowerShell

Ansible

Azure Data Factory

Databricks

Job description

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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. This 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 contributes to modernization activities in an Agile/DevOps operating culture.

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 enterprise 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, 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.

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, 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.

Education

• B.S. degree and 4-8 years of prior relevant experience; or
• Master's degree and 2-6 years of prior relevant experience in data engineering, computer science, information systems, software engineering, mathematics, or a related technical discipline.
• Additional directly related experience may be considered in place of a degree.

Experience

• At least 4 years of relevant experience. [Required]
• At least 3 years of hands-on experience developing, operating, or supporting production data pipelines, data integrations, data warehouses, data lakes, or comparable enterprise data solutions. [Required]
• 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.
• Experience diagnosing production data issues, analyzing logs and metrics, resolving failed jobs or performance problems, and documenting root cause and corrective action.
• 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.
• Working knowledge of PowerShell, Python, and Ansible, with practical familiarity using large language models and AI-enabled tools.

Skills

• Ability to work independently and collaboratively in a high-tempo operational environment.
• Ability to manage competing priorities.
• Ability to communicate technical information clearly.
• Ability to produce complete technical documentation.

Certifications

Must possess and maintain an IAT Level II certification that satisfies applicable DoD cybersecurity workforce requirements. [Required]

Clearance

Active DoD Secret security clearance. [Required]

Other Requirements

• Must be located in, or able to work onsite at Navy Base as required, in one of the following locations: San Diego, California; the Hampton Roads, Virginia area; or Jacksonville, Florida. [Required]
• 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, key performance indicators, and self‑service analytics solutions.
• Experience with Microsoft Power BI and associated DAX knowledge.
• 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, the Risk Management Framework, 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, such as Neo4j, and query languages such as Cypher.
• Experience 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.