Data Engineer - Platform & Self-Service Analytics

Baseten; San Francisco (CA); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

100% coverage of medical, dental, and vision insurance

Generous PTO policy

Paid parental leave

Company-facilitated 401(k)

Exposure to various ML startups

Job summary

A tech-driven AI company in San Francisco is looking for a Data Engineer to build and scale its internal data platform. The successful candidate will design data models, create data pipelines, and ensure data integrity to support strategic decision-making. This position requires experience in data engineering, analytics, and familiarity with tools like Apache Beam and Kafka. The role offers competitive compensation and an opportunity to work within a dynamic team focused on machine learning.

Qualifications

• Understanding of inference metrics such as latency, throughput, token usage, and model performance.
• Experience supporting B2B SaaS and/or consumption-based platforms.
• Application of forecasting and predictive modeling (e.g., ARIMA, Prophet) to business processes.

Responsibilities

• Design and maintain core data models and semantic layers.
• Develop and orchestrate batch and streaming data pipelines.
• Analyze inference and infrastructure telemetry.
• Define and maintain company-wide metrics.
• Enable self-service analytics through agents and tools.
• Ensure data reliability and quality through testing and governance.

Skills

Data modeling

Data pipeline development

Data analytics

Observation tools

Tools

Apache Beam

Kafka

Airflow

OpenTelemetry

Grafana

Job description

A tech-driven AI company in San Francisco is looking for a Data Engineer to build and scale its internal data platform. The successful candidate will design data models, create data pipelines, and ensure data integrity to support strategic decision-making. This position requires experience in data engineering, analytics, and familiarity with tools like Apache Beam and Kafka. The role offers competitive compensation and an opportunity to work within a dynamic team focused on machine learning.