Junior Data Engineer

Benefits:

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

Junior Data Engineer

Position Overview

Meridian Systematics is seeking a Junior Data Engineer to support a National Geospatial-Intelligence Agency (NGA) program that delivers GEOINT data across the enterprise. You will help build, test, and support the data solutions that change how analysts, customers, and end users access, discover, stage, link, produce, and deliver intelligence.

This is a growth role. You will work alongside experienced engineers and build skills in data engineering, cloud platforms, and secure software development.

Responsibilities

• Assist in building, testing, documenting, and maintaining data pipelines and ETL/ELT workflows under the guidance of senior engineers.
• Write and maintain SQL queries and scripts to ingest, transform, validate, and prepare structured and semi-structured data.
• Support data integration from APIs, databases, files, and other approved sources, following established security and authentication practices.
• Run data quality checks, investigate discrepancies, and share findings with the team.
• Monitor scheduled data workflows, troubleshoot routine failures, and ???
• Take part in Agile planning, code reviews, testing, and documentation, following team practices for version control and deployment.

Qualifications

Required

• Active TS/SCI clearance with CI Polygraph.
• Bachelor's degree in computer science, information systems, engineering, mathematics, or a related field; equivalent practical experience may be considered.
• 0–2 years of relevant experience; internships, coursework, and substantial projects count.
• Foundational programming skills in Python and SQL.
• Basic understanding of relational databases, data structures, and common data formats such as CSV and JSON.
• Familiarity with Git and collaborative development, and a willingness to learn automated testing, CI/CD, and production support.
• Ability to review datasets, spot anomalies or inconsistencies, and explain findings clearly.
• Strong attention to detail, clear written and verbal communication, and eagerness to ask questions and learn new tools.

Preferred

• Internship, coursework, or project experience with data pipelines or analytical datasets.
• Exposure to AWS or another cloud platform (storage, compute, or managed data services).
• Familiarity with data modeling, metadata, search, cataloging, or GIS concepts.
• Exposure to Spark, Hadoop, Hive, Elasticsearch, or Tableau.