Senior Data Platform Engineer - Enterprise Systems

Astranis•San Francisco, CA

4d•$145,000 - $210,000•Onsite

About The Position

Astranis is scaling satellite production at a record pace. Building constellations of commercial geostationary spacecraft generates massive amounts of telemetry, manufacturing, supply chain, and application data. To keep our engineers moving fast, we need a unified, scalable data platform and observability infrastructure that brings clarity to every operational detail from the factory floor to launch. We’re looking for a Senior Data Platform Engineer to define, architect, and build our core data architecture, unified logging pipelines, and internal data tools. You will conduct hands-on customer discovery across hardware, software, and operational teams to turn complex requirements into production-ready software tools and establish clear architectural patterns across our data stack. If you're a platform engineer who thrives on customer discovery, systems architecture, and turning raw data into intelligence to scale our fleet, come build with us.

Requirements

Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent technical experience.
5+ years of professional software/data engineering experience with a focus on data infrastructure, data platforms, or backend engineering.
Strong proficiency with Python and solid software design fundamentals.
Proven experience implementing RBAC, Data Governance, and Schema Evolution/Migration strategies in production environments.
Deep database expertise in transactional, relational databases (PostgreSQL schema design, OLTP workflows) as well as columnar databases and analytical data warehouses (BigQuery, Snowflake).
Experience with modern data orchestration and modeling tools (e.g., dbt, Airflow, Prefect, Dagster).

Nice To Haves

Prior experience building data integrations around hardware, PLM, MES, or ERP platforms (Altium, Arena, First Resonance ION, NetSuite).
Background working in hardware-centric environments such as aerospace, automotive, robotics, or complex precision manufacturing.
Experience designing, building, and maintaining robust APIs (RESTful, gRPC) and cloud infrastructure (Docker, Kubernetes/GKE, GCP).

Responsibilities

Define our overarching data architecture, ingestion, storage, and access patterns separating transactional databases (Managed Postgres) from centralized analytical warehouses (BigQuery, Snowflake).
Conduct discovery across the company, working with aerospace engineers, technicians, finance, sales, and software teams to gather requirements and build robust backend data tools and platforms.
Build standardized data pipelines and modeling frameworks (dbt) that stitch together telemetry, supply chain, factory floor (ION), and ERP (NetSuite) data into unified analytical stores for cross-functional reporting.
Build end-to-end pipelines to collect, normalize, and query structured logs, traces, and hardware telemetry across backend services and factory testbeds for real-time system monitoring and debugging.
Establish corporate data governance frameworks, Role-Based Access Control (RBAC), and robust schema evolution strategies to guarantee data security, quality, and backward compatibility.