Senior Software Engineer, Data Platform

You'll architect high-throughput pipelines, establish data quality and reproducibility standards, and build the infrastructure and tooling needed to make data easy to discover, process, label, and use.

What You'll Do

* Architect and build high-throughput data pipelines from scratch.
* Develop pipelines for processing, aligning, transforming, and calibrating complex datasets.
* Build backfill and reprocessing frameworks for historical data.
* Establish dataset lineage, versioning, and reproducibility.
* Build APIs and tooling for dataset discovery and access.
* Develop data-quality metrics, monitoring, and alerting.
* Optimize storage, compression, partitioning, and data access patterns.
* Build internal tools and workflows for ML and data-labeling teams.
* Partner closely with ML engineers to understand and support their data requirements.

What We're Looking For

* 5–8 years of software or data engineering experience.
* Proven ability to architect a data platform or high-throughput pipeline from a blank page.
* Strong Python and data tooling experience, such as PyArrow, Polars, Pandas, NumPy, or SciPy.
* Experience with AWS or another major cloud platform and deploying production data pipelines.
* Experience with a services language such as Go, Rust, or TypeScript.
* Strong understanding of data lineage, versioning, reproducibility, and data quality.
* Experience building backfill and reprocessing systems.
* High ownership and ability to operate independently in a startup environment.
* U.S. citizenship required.

Strong Plus

* Founding or early data-platform engineering experience.
* Experience with sensor, audio, video, telemetry, or geospatial data.
* Airflow, Prefect, MLflow, W&B, or similar tooling.
* Experience building labeling tools or ML data workflows.
* Strong full-stack/generalist capabilities.
* Experience treating datasets as a product, with strong documentation and discoverability.