Principal Data Engineer

True Anomaly•Long Beach, CA

4h•$200,000 - $290,000•Hybrid

About The Position

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. 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.

Requirements

10+ years of experience in data engineering and software engineering field
Strong hands-on Python and SQL experience
3+ years of experience with Snowflake, Databricks, or both
Strong understanding of data engineering, data architecture, data modelling and ELT/ETL
Strong understanding of software engineering practices including Git, testing, CI/CD and code reviews
Demonstrated ability to provide technical leadership and mentor other engineers
Adopt AI-assisted engineering tools to improve productivity and delivery speed

Nice To Haves

Experience with AWS, Azure or GCP
Experience with Airflow, dbt, Kafka or similar technologies
Experience building out Lakehouse architectures
Experience with data governance, lineage and observability
This is a hands-on Principal level engineering role. The successful candidate should be comfortable writing code, designing architecture, solving difficult technical problems, and influencing best data practices across the company

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
Collaborate across engineering, AI/ML, analytics, product and business teams to translate requirements into reliable, scalable data solutions and products and contribute to technical design decisions
Leverage AI-assisted engineering tools while contributing to data engineering technical excellence through code reviews, reusable frameworks, documentation, knowledge sharing, and mentoring other data engineers
Mentor Junior and Senior Data Engineers and provide technical guidance across the engineering teams