Data Engineer

About this role

SteerBridge 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. Position Overview SteerBridge seeks a highly skilled and motivated Data Engineer II to join our team supporting the F-35 AI/ML Spares Project. As the most advanced fighter jet in the world, the F-35 strengthens national security, enhances global partnerships, and powers economic growth. Our F-35 AI/ML Spares Project applies advanced computational analytics to revolutionize supply chain management in the aerospace industry — harnessing the power of AI/ML to increase parts availability, reduce maintenance wait times, and maximize aircraft availability. In collaboration with the National Center for Manufacturing Sciences (NCMS), we are on a mission to deliver exceptional solutions that will redefine operational readiness for the F-35 program and beyond. In this mid-level role, you will build and maintain AWS-based ETL/ELT pipelines, curated analytical datasets, and reporting workflows that support operational decision-making. You will design scalable data infrastructure that powers business intelligence, machine learning, and operational analytics — performing data engineering tasks on-site within the existing systems of record with multiple databases. This position also involves mentoring and collaborating with Marines at the squadron level, requiring a deep understanding of squadron-specific operations and a commitment to improving data entry and indexing practices. You will be a crucial link between our existing systems and data development, collaborating closely with data scientists, analysts, and operational partners. Key Responsibilities • Lead end-to-end data pipeline operations — design, develop, and maintain robust ETL/ELT pipelines on AWS (AWS Glue, Amazon Redshift, Amazon S3) using modern orchestration tools such as Apache Airflow, dbt, or Prefect. • Use Azure Databricks (Spark) and Azure Data Factory to manage and schedule data pipelines and workflows. • Build and optimize data models in cloud data warehouses (Snowflake, BigQuery, or Redshift); maintain data in S3 buckets and Blob storage. • Integrate data from diverse sources including REST/SOAP APIs, event streams (Kafka), relational and non-relational databases, and SaaS platforms. • Create, index, query, and update SQL tables/servers; run and update Python and/or JavaScript code to parse data. • Monitor pipeline health, enforce data quality controls (schema validation, null checks, duplicate detection), troubleshoot data issues, and implement alerting and observability best practices. • Develop and implement data acquisition, quality assurance, and management protocols; document all data collection, cleaning, and analyses for internal and external users. • Use schedulers and APIs to obtain near real-time data; automate workflows and processes using Python or other scripting languages. • Partner with data scientists and analysts to deliver clean, well-documented datasets and data products; collaborate with and support the data science team to produce deliverables. • Contribute to data governance standards including lineage, cataloging, and access controls. • Mentor and collaborate with Marines at the squadron level to improve data entry and indexing practices. • Assist with maintenance and development of internal analytics data architecture. • Design, write, and disseminate innovative and visually appealing reports for diverse audiences. • Participate in code reviews, architecture discussions, and cross-functional planning sessions. • Evaluate and recommend new tools and technologies to improve the data platform. Required Qualifications Education & Experience • 3–5 years of professional experience in data engineering or a closely related role. • Bachelor's Degree in Computer Science or related field; three (3) years of additional relevant experience may substitute for education (minimum six years total experience without degree). • U.S. Citizenship required. • Active security clearance or the ability to obtain one is required. Technical Skills • Strong proficiency in Python (PySpark, pandas) and SQL for data processing and pipeline development; SQL fluency including CTEs, window functions, and complex joins. • Hands-on experience with at least one cloud data warehouse (Snowflake, BigQuery, or Redshift). • Experience configuring or monitoring data pipelines in cloud platforms (AWS preferred; Oracle, Azure, Google also considered). • Familiarity with analytics deployment architectures including Python, containerized Docker, and Kubernetes. • Experience with Spark/Databricks for streaming data analytics, with preferred experience in graph data, machine learning, and AI applications. • Experience using Azure Data Factory to schedule pipelines and manage data flows. • Ability to connect and work with APIs (REST, SOAP, HTTP methods). • Experience with workflow orchestration tools such as Apache Airflow, dbt, or Prefect. • Solid understanding of data modeling concepts: star schema, data vault, medallion architecture, data lineage, and source-to-target mapping. • Familiarity with data visualization tools including Tableau, Power BI, Elasticsearch/Kibana, R, or Alteryx. • Experience with version control (Git), CI/CD practices, and production deployment workflows. • Experience inte