Senior Software Engineer, Data

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 is seeking a Senior Software Engineer, Data to support the Modern Disability Claims program. This senior role owns the software engineering practice that surrounds our data platform, including internal tools, APIs and services that expose or consume data from the pipeline, and shared libraries/frameworks, while setting the standards and rigor (design patterns, automated testing, refactoring) that raise the overall engineering quality of the data pipeline. This is a backend-focused role distinct from both the Data Engineer, who owns the pipeline logic itself, and the Software Engineer, who builds full-stack, user-facing features.

Key Responsibilities

• Design, build, and maintain internal tools, APIs, shared libraries, and frameworks that expose and consume data from the Modern Disability Claims (MDC) data pipeline.

• Establish and enforce software engineering standards across platform tooling, including design patterns, clean architecture, code quality, refactoring practices, and code review standards.

• Establish and champion automated testing practices, including unit and integration testing with pytest, to improve the reliability and maintainability of data platform tooling.

• Partner with Data Engineers to identify pipeline components that would benefit from stronger software engineering practices and lead efforts to improve their design, testing, and maintainability.

• Package, version, distribute, and document Python libraries, APIs, services, and internal tools for reliable use across engineering teams.

• Troubleshoot and resolve complex software defects in internal tools, services, and components supporting the data pipeline.

• Mentor engineers on software design, testing, and refactoring best practices while contributing to sprint planning, technical priorities, and delivery status.

Required Qualifications

• Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidate must also be able to obtain and maintain the security clearance required for the role, including a Public Trust clearance; an active Secret or Top Secret clearance also satisfies this requirement.

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent experience.

• 6+ years of experience in software engineering, including the development and maintenance of production-quality software systems.

• Deep proficiency in Python, including type hints and static typing tools such as mypy, modern packaging tools such as Poetry or setuptools, and clean architecture and design pattern principles.

• Extensive experience developing automated unit and integration tests with pytest, with a demonstrated ability to establish and improve testing practices across a team.

• Experience designing and building APIs and backend services using standard software development practices, including Git, code review, version control, and collaborative development workflows.

• Strong communication and collaboration skills, with demonstrated experience mentoring engineers and partnering with data engineering teams to improve shared software design and code-quality standards.

Preferred Qualifications

• Familiarity with data pipelines, ETL/ELT concepts, and related data engineering workflows.

• Experience with cloud data platforms such as AWS, Azure, or GCP.

• Experience with CI/CD pipelines, automated testing, and quality gates.

• Experience supporting healthcare, insurance, benefits administration, or federal programs.