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Salary: USD 200,000 - 290,000 / annual
True Anomaly is building autonomous spacecraft, advanced payloads, mission software, and space-based interceptors to secure the space environment and counter threats. We are seeking a Principal Data Engineer to provide hands-on technical leadership in designing, building, and evolving scalable data platforms that support the company's mission of space superiority.
In this role, you will be responsible for solving complex data engineering challenges, establishing engineering standards, and guiding the technical direction of True Anomaly's Enterprise Data Platform. You will 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. You will build and optimize ELT/ETL processes and data models using cloud data platforms (Snowflake, Databricks, or Redshift) with a focus on performance, scalability, reliability, and cost efficiency.
Key responsibilities include establishing and applying engineering best practices for data quality, testing, monitoring, observability, CI/CD, version control, security, and production reliability. You will own data engineering projects end-to-end, from technical design and development through deployment, production support, troubleshooting, and continuous improvement. You will collaborate across engineering, AI/ML, analytics, product, and business teams to translate requirements into reliable, scalable data solutions. Additionally, you will mentor junior and senior data engineers, provide technical guidance across engineering teams, and leverage AI-assisted engineering tools to improve productivity and delivery speed.
The ideal candidate is a strong hands-on engineer with 10+ years of experience in data engineering and software engineering, deep expertise in Python and SQL, and 3+ years of experience with Snowflake, Databricks, or both. You should have a strong understanding of data engineering, data architecture, data modeling, and ELT/ETL, as well as software engineering practices including Git, testing, CI/CD, and code reviews. Preferred qualifications include experience with AWS, Azure, or GCP; Airflow, dbt, Kafka, or similar technologies; lakehouse architectures; and data governance, lineage, and observability.
