Data Platform Engineer — Scale Pipelines & Governance

We Love AI Jobs; San Francisco (CA); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Stock options

Comprehensive benefits

Job summary

Sigma Computing is building out its Data Platform team to own data architecture across Snowflake and Databricks, and to develop scalable ETL pipelines for internal and demo use cases. Reporting to leadership, you’ll work across product, engineering, and GTM to deliver high-visibility projects in a fast-paced startup environment.

The role emphasizes a builder mindset, data governance, and collaboration with analytics and infra teams to enable trusted insights and scalable data assets.

Qualifications

• Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks)
• Strong communication and collaboration skills, ability to partner with Analytics and Infrastructure Engineering teams
• Experience deploying data governance frameworks with a scalable and repeatable process
• 3+ years of relevant experience working in a data engineering role

Responsibilities

• Architect and manage production data pipelines in Snowflake and how they are consumed in Sigma
• Build foundational processes for scaling demo asset data across various Cloud Data Warehouses
• Scale Terraform deployments across all Snowflake assets
• Continue to advance data governance policies
• Work cross functionally with Product, Engineering, GTM teams

Job description

Sigma Computing is building out its Data Platform team to own data architecture across Snowflake and Databricks, and to develop scalable ETL pipelines for internal and demo use cases. Reporting to leadership, you’ll work across product, engineering, and GTM to deliver high-visibility projects in a fast-paced startup environment.

The role emphasizes a builder mindset, data governance, and collaboration with analytics and infra teams to enable trusted insights and scalable data assets.