Backend Engineer - Data Management Services
Team: Cockpit
Location: Golden, CO or San Francisco
Commitment: Full time
Workplace Type: onsite
Salary:
About this Role:
- Design and build backend services for data ingest, processing, and delivery that move payload data from ground stations and other sources into Cockpit and out to customer endpoints.
- Implement and improve data pipelines and APIs with a strong focus on data correctness, traceability, performance, and reliability.
- Own and evolve backend components such as connectors, processing jobs, and delivery services that other Cockpit teams and customer‑facing tools depend on.
- Collaborate with other Cockpit teams and stakeholders (mission management, mission operations, space infrastructure, customer operations) to make sure on‑orbit tasking and ground data flows work smoothly together.
- Support internal users of Cockpit’s data services by improving APIs, debugging tricky data issues, and strengthening observability (metrics, logs, dashboards).
- Have the opportunity to take part in spacecraft operations through SatDevOps rotations, occasionally helping investigate data‑related anomalies and supporting real‑time incident response when needed.
Must Haves:
- Strong Python development experience in a production environment.
- Experience with Docker and container‑based development.
- Hands‑on experience with backend web development frameworks (e.g., Django, Flask, FastAPI, etc.).
- Proven API design skills (designing, documenting, and maintaining HTTP/GraphQL/REST‑style APIs).
- Practical experience working with databases and data‑centric backend services.
Nice to Haves:
- Experience with Django and/or GraphQL.
- Strong database fundamentals and experience with PostgreSQL or similar relational databases.
- Exposure to message-oriented middleware or event streaming systems (e.g., NATS, NATS JetStream).
- Experience building or maintaining event-driven data pipelines, ETLs, or stream processing systems.
- Familiarity with metrics computation, data transformation, and/or time-series data stores (e.g., MongoDB time-series collections, InfluxDB, TimescaleDB).
- Exposure to Kubernetes and cloud-native deployments in production (GCP and/or AWS).
- Background in mission-critical, distributed, or real-time systems, especially data-intensive ones (space or otherwise).
- Experience collaborating with international, distributed teams across time zones and cultures.
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