Data Platform Engineer for AI Metrics & Observability

Baseten; United States; Remote; USD 100,000 - 150,000; Full time

Benefits offered by this job

Competitive compensation, including 1e

100% coverage of medical, dental, and視

Flexible PTO policy including company冬

Paid parental leave

Fertility and family-building stipend

Company-facilitated 401(k)

Exposure to ML startups

Job summary

Baseten is 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.

Qualifications

• Design and maintain core data models and semantic layers.
• Develop batch and streaming data pipelines using Beam, Kafka, Airflow, or similar frameworks.
• Analyze inference and infrastructure telemetry data from OpenTelemetry and Grafana for insights.

Responsibilities

• Design and maintain core data models and semantic layers.
• Develop and orchestrate batch and streaming data pipelines using technologies such as Apache Beam, Kafka, Airflow, or similar frameworks.
• Analyze inference and infrastructure telemetry, including data from OpenTelemetry, Grafana, and other observability tools.
• Define and maintain company-wide metrics across product usage, performance, and customer lifecycle.
• Enable self-service analytics through agents and tools, with well-structured semantic layers and context.
• Ensure data reliability and quality through testing, documentation, and governance.

Skills

Data engineering

Analytics

Data modeling

Metrics definition

Self-service analytics

Tools

Apache Beam

Kafka

Airflow

OpenTelemetry

Grafana

Job description

Baseten is 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.