Data Analyst

United States·Cherry PointFull-timemid

Data ScienceData AnalystDataData & AI

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Quick Summary

Overview

SteerBridge Strategies is a modern technology company delivering innovative, mission‑focused solutions to the U.S. Government and private sector. Leveraging deep expertise in federal acquisition,

Technical Tools

Data ScienceData AnalystDataData & AI

SteerBridge Strategies is a modern technology company delivering innovative, mission‑focused solutions to the U.S. Government and private sector. Leveraging deep expertise in federal acquisition, digital transformation, and emerging technologies, we deliver agile, commercial‑grade capabilities that accelerate operational effectiveness and drive measurable mission success.

At the core of SteerBridge is our people—especially the veterans whose leadership, problem‑solving mindset, and commitment to excellence elevate every project we support. We don’t simply hire exceptional talent; we cultivate it, creating meaningful career pathways for veterans, military spouses, and professionals who share our passion for advancing technology and strengthening the missions we serve.

SteerBridge Strategies is seeking a highly skilled Data Analyst to support mission-critical operations in a secure, controlled data environment. This role focuses on advanced data analysis, automation, and reporting to drive informed decision-making at leadership levels.

The ideal candidate will have strong SQL expertise, experience working with large datasets, and the ability to translate complex data into actionable insights.

Responsibilities

~1 min read

Analyze large, relational datasets to identify trends, inefficiencies, and performance gaps
Translate raw data into actionable insights to support leadership decision-making
Identify degraders, shortages, and operational inefficiencies

Write clean, efficient, and production-ready SQL (Amazon Redshift, Oracle SQL Developer)
Utilize advanced SQL techniques (CTEs, window functions, complex joins, aggregations)
Optimize queries for performance and scalability
Troubleshoot and resolve data discrepancies across multiple data sources

Implement automated validation checks (row counts, duplicates, completeness, integrity)
Ensure accuracy and consistency of data before reporting
Identify and resolve root causes of data inconsistencies

Support and maintain ETL pipelines and data workflows
Build automated processes for data ingestion, transformation, and validation
Implement scheduling/orchestration tools (cron, AWS services, Airflow, or equivalent)
Ensure processes run without manual intervention