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Senior Data Engineer

Meridian Systematics Fairfax County, Virginia, United States · $145K–$175K/yr

Engineering Services · 11-50 employees

7 h ago
data-engineer Senior (5-10 yrs) Full-time United States
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About the role

Lead the architecture, design, and operation of scalable data pipelines and ETL/ELT processes for mission operations. Collaborate with stakeholders to define requirements, guide technical decisions, and ensure data quality and security across production systems.

What they look for

Data engineering ETL/ELT Python Scala Java Cloud platforms Data modeling API integration Data quality Git CI/CD Agile Database performance System architecture Technical leadership Mentoring

Requirements

Requires an active TS/SCI clearance with CI Polygraph and a bachelor's degree with at least 5 years of relevant experience. Candidates must demonstrate proficiency in Python, Scala, or Java and possess strong experience in data modeling and pipeline development.

Benefits

401(k) Dental insurance Flexible schedule Health insurance Paid time off Parental leave

Full description

Benefits:

  • 401(k)
  • Dental insurance
  • Flexible schedule
  • Health insurance
  • Paid time off
  • Parental leave

Senior Data Engineer

Position Overview

Meridian Systematics is seeking a Senior Data Engineer to support a National Geospatial-Intelligence Agency (NGA) program that delivers GEOINT data across the enterprise. You will lead the design of the cloud-based data platforms that change how analysts, customers, and end users access, discover, stage, link, produce, and deliver intelligence.

You will guide technical decisions, mentor engineers, and work across mission and engineering teams.

Responsibilities

  • Lead the architecture, design, development, and operation of scalable data pipelines and ETL/ELT processes for analytics, reporting, and mission operations.
  • Design and oversee API connectors and integrations that securely ingest data from internal platforms and external services.
  • Set engineering approaches for data processing, storage, and database performance to meet scale, reliability, and latency needs.
  • Establish and improve data quality, validation, monitoring, and governance practices across production data products.
  • Partner with mission stakeholders, analysts, architects, and product teams to define requirements and guide solutions.
  • Lead diagnosis and resolution of complex pipeline, integration, and production performance incidents.
  • Work with security and compliance teams to build required protections and controls into data systems.
  • Maintain architecture and operational documentation, and mentor engineers through design discussions and code reviews.
  • Contribute to Agile planning, helping the team break down work and manage technical dependencies.
  • Evaluate platform and tooling choices and recommend improvements to data architecture and engineering practices.

Qualifications

Required:

  • Active TS/SCI clearance with CI Polygraph.
  • Bachelor's degree with 5+ years of relevant experience, or a related master's degree with 3+ years. Degree in computer science, information systems, engineering, mathematics, or a related field.
  • Proven ability to design, write, review, and support production code in Python, Scala, Java, or a comparable language, using Git, automated testing, and CI/CD.
  • Strong experience with ETL/ELT architecture, data modeling, data quality, and secure API integrations, including troubleshooting authentication and data exchange issues.
  • Experience delivering and operating scalable production pipelines across structured, semi-structured, and unstructured data.
  • Sound judgment selecting data architectures and patterns for complex, evolving datasets.
  • Ability to own complex work from requirements and design through production operation.
  • Experience leading technical collaboration with analytics, data science, product, security, or mission teams, and mentoring other engineers.
  • Clear written and verbal communication, including explaining technical decisions and tradeoffs.

Preferred:

  • Knowledge of metadata standards.
  • Experience with search tools, search results organization, indexing, and how metadata organization affects catalog content.
  • Experience with GIS-related applications.

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