Data Engineer
US$180,000 – US$250,000 / yr base salary
Posted 18 Mar 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- Hybrid
- Contract
- Full-time
| Base salary | US$180,000 – US$250,000 / yr |
|---|
ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.
THE ROLE
We’re hiring a Data Engineer to build and scale Baseten’s internal data platform. This role sits at the intersection of data engineering, analytics, and data science, transforming raw product and business data into reliable datasets that power decision-making.
You’ll design the data models, pipelines, and analytics infrastructure that enable teams across Product, Engineering, Finance, Marketing, and Sales to understand usage and performance. This includes working with AI inference, infrastructure, and observability data to generate insights about the product, business operations and platform economics.
You’ll partner closely with stakeholders to build robust, scalable pipelines, define company-wide metrics that inform strategy and planning.
RESPONSIBILITIES
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Design and maintain core data models and semantic layers
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Develop and orchestrate batch and streaming data pipelines using technologies such as Apache Beam, Kafka, Airflow, or similar frameworks
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Analyze inference and infrastructure telemetry, including data from OpenTelemetry, Grafana, and other observability tools
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Define and maintain company-wide metrics across product usage, performance, and customer lifecycle
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Enable self-service analytics through agents and tools, with well-structured semantic layers and context
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Ensure data reliability and quality through testing, documentation, and governance
PREFERRED QUALIFICATIONS
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Understanding of inference metrics such as latency, throughput, token usage, and model performance
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Experience supporting B2B SaaS and/or consumption-based platforms