SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 163,500 - 228,500 / annual
Neros Technologies is a defense technology company designing and manufacturing high-performance unmanned systems tested in combat and iterated at startup speed. The company is rebuilding America's drone industrial base with a culture focused on speed, hands-on execution, and closing the gap between design and deployment.
As Senior Data Platform Engineer, you will own the autonomy data pipeline end-to-end. This is a greenfield role where you will architect and operate the storage, catalog, and query infrastructure that powers every autonomy test, simulation run, and machine learning dataset at Neros.
Key responsibilities include:
- Building the path for flight data recovery from field vehicles, including triggered capture, prioritized upload, and resumable transfer with integrity verification
- Processing raw logs into a usable corpus: decoding, time-aligning multi-sensor and video streams, validating, and quarantining malformed data
- Designing the catalog and tag model to index the corpus, and standing up cloud storage and database infrastructure
- Building a query layer enabling engineers to retrieve flights matching complex conditions (e.g., loss of target lock at terminal stage under high glare within 90 days) with playable video returned in seconds
- Serving logs to evaluation harnesses with stable ordering, exact time alignment, and reproducible results across thousands of flights
- Creating versioned, immutable datasets from catalog queries with lineage tracking for exact reproducibility months later
You will own the architecture, operating cost, and compliance posture of this critical infrastructure.
REQUIREMENTS:
- 5+ years building production data or backend infrastructure, including at least one system owned end-to-end from initial design through ongoing operation
- Direct experience with large-scale log or sensor data (multi-terabyte and growing) with video and multiple synchronized sensor streams (rosbag, MCAP, HDF5, Parquet, or equivalent formats)
- Designed and owned a data schema, index, or catalog queried daily by other engineers, with experience managing at least one migration
- Strong Python, plus SQL and working ownership of a relational database (PostgreSQL or equivalent) in production
- Practical experience with cloud object storage and compute (Azure, AWS, or GCP) with ability to provision and operate independently
- Experience with distributed or parallel batch processing and job orchestration (Spark, Ray, Dask, Airflow, Dagster, or equivalent) across large data volumes
- Working knowledge of time synchronization and alignment across sensor streams, and deterministic, reproducible processing of recorded data
- Track record of building internal tooling adopted by other engineers, with demonstrated ability to iterate design based on actual usage
NICE TO HAVE:
- Log or data infrastructure built for robotics, autonomous vehicles, aerospace, or defense programs
- Experience handling video at scale (transcoding, frame-accurate seeking, streaming playback)
- Direct Azure experience, infrastructure-as-code (Terraform or Bicep), and cloud budget responsibility
- Prior work in export-controlled, GovCloud, or IL4/IL5 environments; familiarity with CMMC and ITAR
- Experience connecting data pipelines to labeling vendors, model training, experiment tracking, or model registry workflows
