Principal Data Engineer

About the role

Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it.

OUR MISSION

True Anomaly delivers decisive capabilities for space superiority. We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors — enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground.

OUR VALUES

- Be the offset. We create asymmetric advantages with creativity and ingenuity.

- What would it take? We challenge assumptions to deliver ambitious results.

- It’s the people. Our team is our competitive advantage and we are better together.

BENEFITS & PERKS*

- Best-in-class healthcare: 100% company-paid medical, dental, and vision coverage for you and your dependents, with HSA/HRA options

- Generous time off: Flexible Time Off (FTO) for exempt employees, accrued PTO of up to 25 days for non-exempt employees, plus 12 paid holidays; Parental Leave; Sick Leave

- Fuel for your day: Daily catered lunch and unlimited snacks for in-office employees

- And more: 401(k) retirement plan, fitness reimbursement, and Dog Fridays

- Equity participation: Equity is included as part of our total compensation package, giving you an opportunity to share in the company’s success.

*Do not apply to fixed term and temporary roles

YOUR MISSION

We are looking for a Principal Data Engineer to provide hands-on technical leadership in designing, building and evolving scalable data platforms. This role will be responsible for solving complex data engineering challenges, establishing engineering standards, and guiding the technical direction of True Anomaly’s Enterprise Data Platform.

The ideal candidate is a strong hands-on engineer with deep experience in Python, SQL, and modern cloud data platforms such as Snowflake, Databricks or Redshift.

This role will embrace the use of AI to aid data engineering and improve productivity, including leveraging AI-assisted development tools, automation and systems to accelerate pipeline development, improve code quality and optimize workflows.

RESPONSIBILITIES

- Design, develop and maintain scalable data pipelines and data products using Python, SQL and modern data engineering practices, supporting batch, streaming, analytics, and AI/ML workloads

- Build and optimize ELT/ETL processes and data models using cloud data platforms with a focus on performance, scalability, reliability and cost efficiency

- Establish and apply engineering best practices for data quality, testing, monitoring, observability, CI/CD, version control, security, and production reliability

- Own data engineering projects end-to-end, from technical design and development through deployment, production support, troubleshooting, and continuous improvement