Senior Data Platform Engineer

Description

The company designs and manufactures high-performance unmanned systems for defense, is rebuilding the US drone industrial base, and has its systems tested in combat. It moves quickly, works hands-on, and focuses on shortening the time from design to fielding.

The company wants to give Western forces drone capability in months rather than years, and is hiring engineers, operators and builders who take full ownership of their work.

This is a greenfield role that owns the autonomy data pipeline from recovering flight data in the field, through cloud storage, to searchable and replayable access at scale. You will build the storage, catalog and query infrastructure that autonomy tests, simulation runs and machine learning datasets all rely on, and you will own its architecture, running cost and compliance.

Responsibilities

• Build the route that returns flight data from the field, with triggered capture on the vehicle, uploads ranked so the most valuable flights arrive first, and resumable transfers with integrity checks.
• Turn raw logs into a clean corpus by decoding them, aligning timing across multiple sensor and video streams, validating the results, and isolating malformed data before downstream users reach it.
• Design the catalog and tagging model that indexes the corpus, and set up the cloud storage and database that hold it.
• Build a query layer that lets an engineer pull every flight matching a condition, such as loss of target lock during terminal stage under high glare within the last 90 days, with playable video returned within seconds.
• Feed logs to the evaluation harness in a stable order with exact time alignment and repeatable results, so regression jobs can cover thousands of flights at once.
• Generate versioned, immutable datasets from catalog queries and record their lineage, so any training set can be rebuilt exactly months later.

Requirements

• At least 5 years building production data or backend infrastructure, including one system you owned from initial design through ongoing operation.
• Hands-on work with large recorded log or sensor datasets, multi-terabyte and growing, that include video and several synchronized sensor streams in formats such as rosbag, MCAP, HDF5, Parquet or similar, rather than row-based business data.
• You have designed and owned a schema, index or catalog that other engineers queried daily, lived with its consequences, and carried out at least one migration.
• Strong Python and SQL, plus hands-on ownership of a production relational database such as PostgreSQL or an equivalent.
• Practical experience running cloud object storage and compute on Azure, AWS or GCP, and provisioning and operating it yourself without a dedicated platform or DevOps team.
• Experience with distributed or parallel batch processing and job orchestration, such as Spark, Ray, Dask, Airflow, Dagster or similar, across large volumes of recorded data.
• Working knowledge of time synchronization across sensor streams and of deterministic, reproducible processing of recorded data.
• A record of building internal tools that other engineers adopted, including a case where you changed the design based on how people actually used it.
• Experience with infrastructure built for robotics, autonomous vehicles, aerospace or defense programs, where replay determinism, time alignment and multi-sensor logs were core problems from the start.
• Experience handling video at scale, including transcoding, frame-accurate seeking and streaming playback of recorded footage to engineers.
• Direct Azure experience, infrastructure defined as code with Terraform or Bicep, and prior responsibility for a cloud budget where storage tiering and egress costs mattered.
• Work in export-controlled, GovCloud or IL4/IL5 environments, or familiarity with CMMC and ITAR data handling obligations.
• Experience connecting a data pipeline to a labeling vendor or internal labeling tooling, or to model training, experiment tracking and model registry workflows.

Conditions

The base salary range is $163,500 to $228,500 USD. This is an estimate across many compensation factors and covers base salary only. The actual figure may vary with experience, education or training, critical skills and business considerations.

The company does not consider race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status or disability status in hiring decisions.

Benefits

• Highly competitive equity grants form part of the total compensation package.