Senior Data Engineer

As a Senior Data Engineer (DE) at Planet, you will own, architect and build production, enterprise-scale data ecosystems using modern cloud technologies, to power mission-critical, customer-facing products. You will act as a strategic partner to cross-functional stakeholders, translating complex requirements into robust, scalable solutions.

You will build and design data solutions end to end: from high-level architecture and implementation to CI/CD, orchestration automated QA, and seamless integration into production systems. You'll be a senior member of the Data Team within the Software Engineering organization, which is made up of data scientists, engineers and analysts working on similar tasks across Planet domains.

Your scope will focus on the architecture and evolution of data systems supporting our global monitoring products. These products are vital offerings designed to provide persistent, high-cadence monitoring and active intelligence, particularly for our Defence and Intelligence customers. You will collaborate closely with leadership across Product and Engineering to ensure some of our most sophisticated customers have the data required for global security and rapid decision-making.

This role is ideal for an expert data engineer looking to lead the evolution of complex systems and deliver transformative technology to the defense sector. The ideal candidate is an independent operator who thrives in a dynamic, global environment and is deeply passionate about Planet's mission and national security solutions.

This is a full-time, hybrid role which will require you to work from our Washington DC or Denver CO office 3 days per week.

- Architect and oversee robust, high-availability data pipelines while establishing the standards for maintaining, troubleshooting, and optimizing existing ecosystems.

- Collaborate with global product, commercial and engineering leads and peers to design and execute a long-term data strategy for products in your scope.

- Drive high-level mentorship, technical design reviews, and architectural integrity across the Data Team while setting standards for code quality.

- 10+ years of relevant experience in data engineering with a track record of technical leadership.

- Expertise in designing and implementing end-to-end data architectures for global-scale, customer-facing solutions, with a focus on data integrity and efficiency.

- Expert-level proficiency in Python and SQL for complex ETL/ELT pipeline construction, including event-driven data architectures.

- Proactive, self-starter mindset with the ability to lead problem-solving initiatives in a dynamic, high-stakes environment.

- Exceptional communication skills, with the ability to translate between technical execution and high-level business requirements.

- Deep experience in maintaining enterprise-grade, peer-reviewed codebases and advanced CI/CD workflows using GitLab CI, Docker, and Kubernetes.

- Significant experience with cloud-native architectures (GCP preferred).

- Experience tuning storage formats such as Parquet to ensure sub-second query performance for consumers.

- Experience using modern data tooling (e.g. dbt) for pipeline inputs to customer-facing production systems.

- Experience leveraging Infrastructure as Code tooling (e.g. Terraform) to manage cloud architecture.

- Experience architecting solutions for geospatial datasets.

- Knowledge of earth observation and/or satellite operation concepts.