Senior Software Engineer, Data Platform (Los Angeles/Remote)
Rheaction · United States · $200k – $240k · posted today ago
Listing supplied by Himalayas. 101 Careers did not originate this post and applications are handled by the employer.
About this role
Location: Remote — Los Angeles area preferred
Employment: Full-time
Experience: 5–8 years
Compensation: $200,000–$240,000 + 0.25%–0.5% equity
Work Authorization: U.S. citizenship required
About the Role
We're looking for a Senior Software Engineer, Data Platform to build and own a data platform from the ground up.
This is a highly autonomous, zero-to-one role focused on turning large volumes of complex, real-world data into clean, consistent, and reliable datasets for machine learning and product teams.
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.
Originally posted on Himalayas
