Analytics Engineer I (Entry-Level) (3897)
Navarro Inc. · Oak Ridge, Tennessee, United States · Posted Jul 6, 2026
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Navarro Research and Engineering is recruiting an Analytics Engineer I (Entry-Level) (3897) in Oak Ridge, TN.
Navarro Research & Engineering is an award-winning federal contractor dedicated to partnering with clients to advance clean energy and deliver effective solutions for complex challenges in the nuclear and environmental fields. Joining Navarro means being a part of an exceptional team committed to quality and safety while also looking for innovative strategies to create value for the client’s success. Headquartered in Oak Ridge, Tennessee, Navarro has active programs in place across the nation for DOE/NNSA, NASA, and the Department of Defense.
Position Summary
The Analytics Engineer I (Entry-Level) will support Navarro’s Data & Analytics team by helping build and maintain data pipelines, assisting with reporting and dashboarding efforts, and contributing to applied AI projects. This role is well suited for an early-career professional interested in growing into a strong analytics or applied AI contributor, including work involving AI/ML techniques to extract, structure, and validate key information from unstructured documents.
Responsibilities
Assist in designing, building, and maintaining data pipelines and ETL/ELT processes.
Write and optimize SQL queries to extract, transform, and analyze data from multiple sources.
Support the development of dashboards and reports using Excel and other business intelligence tools.
Use Python and/or R to automate data workflows, clean datasets, and perform exploratory analysis.
Build and support AI/ML-driven workflows for extracting key text and structured data from documents, including NLP, LLM-based extraction, and OCR plus ML pipelines.
Collaborate with data scientists, analysts, and business stakeholders to understand data and applied AI project needs.
Help document data models, pipeline logic, and AI/ML workflow processes.
Contribute to data quality checks and validation processes for both traditional data and AI-generated outputs.