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Planet designs, builds, and operates the world's largest constellation of imaging satellites, delivering unprecedented earth observation data to commercial, environmental, humanitarian, and defense sectors. As a Senior Data Engineer, you will architect and own production, enterprise-scale data ecosystems using modern cloud technologies to power mission-critical, customer-facing products.
You will serve as a strategic technical partner to cross-functional stakeholders, translating complex requirements into robust, scalable solutions. Your primary focus will be architecting and evolving data systems supporting Planet's global monitoring products—vital offerings for defense and intelligence customers requiring persistent, high-cadence monitoring and active intelligence for global security and rapid decision-making.
Key responsibilities include architecting and overseeing high-availability data pipelines while establishing standards for maintenance, troubleshooting, and optimization; collaborating with global product, commercial, and engineering leaders to design and execute long-term data strategy; and driving mentorship, technical design reviews, and architectural integrity across the Data Team while setting code quality standards.
You will build and design data solutions end-to-end: from high-level architecture and implementation to CI/CD, orchestration, automated QA, and seamless production integration. This role requires deep expertise in designing end-to-end data architectures for global-scale, customer-facing solutions with focus on data integrity and efficiency. You must be expert-level proficient in Python and SQL for complex ETL/ELT pipeline construction, including event-driven architectures, and have significant experience with cloud-native architectures (GCP preferred), enterprise-grade codebases, advanced CI/CD workflows (GitLab CI, Docker, Kubernetes), and storage format optimization (Parquet) for sub-second query performance.
The ideal candidate is an independent operator thriving in dynamic, global environments with 10+ years of data engineering experience and a track record of technical leadership. Preferred qualifications include experience with modern data tooling (dbt), Infrastructure as Code (Terraform), geospatial dataset architecture, and earth observation/satellite operation concepts. This is a full-time hybrid role requiring 3 days per week in either the Washington DC or Denver CO office.
