Data Engineer

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

# Data EngineerSigmaSan Francisco, CAFull-time$140,000 – $180,000 / yearUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageThis data platform role builds the architecture and pipelines that support trusted company insights and product demos. You’ll work with Snowflake and Databricks, establish governance processes, and collaborate with teams across Sigma on new data projects.* Permanent* On-site* 3+ years### Skills and expertiseSnowflakeDatabricksData pipelines and ETLAPIsFivetranDagsterTerraformdbt### Key responsibilities* Architect and manage production data pipelines and their consumption in Sigma.* Build processes to scale demo data assets across cloud data warehouses.* Expand Terraform deployments and advance data governance practices.## How this job comparesCompared with 256 open mid-level data jobs on October 10, 2026.Pay: This job pays $140K to $180K a year. The 67 open mid-level data jobs that publish US pay start at $126K on average, so this job starts about 11% higher.Similar open jobs: We Love AI Jobs lists 256 open mid-level data jobs at 104 companies.Remote work: This job is on site. 91 of the 256 mid-level data jobs (36%) are remote.AI in this role: Low. The company works with AI, but AI is a small part of this role's daily work. The role builds data infrastructure and pipelines for analytics and demo use cases. The posting does not assign work on AI models, AI tooling, or AI products.## Full descriptionData Engineer, Data PlatformAbout the RoleWe are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects.If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat!What You Will Be Doing• Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma (Tech we use: Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane)• Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses• Scale our terraform deployment across all of our Snowflake assets• Continue to advance our data governance policies• Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levelsQualifications We Need• 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. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success.• Experience deploying data governance frameworks with a scalable and repeatable process• Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that• 3+ years of relevant experience working in a data engineering role• Startup experienceQualifications We Want (also, skills you’ll learn!)• A drive to continuously learn (and share those learnings) about the evolving data ecosystem• Familiarity with dbt• Advanced knowledge python knowledge• Advanced knowledge and strong opinions around orchestrators (e.g., Astronomer, Airflow, Dagster)• Advanced knowledge of working with public clouds (e.g., AWS, GCP)Additional Job detailsThe base salary range for this position is $140k - $180k annually.Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for stock options, as well as a comprehensive benefits package.About us:Sigma is the AI Apps and agentic analytics platform built on the cloud data warehouse. Business and technical teams use Sigma to explore live data, build intelligent applications, and automate critical workflows all without moving data or breaking governance. Sigma supports a spreadsheet interface, SQL, Python, and native AI in a single governed workspace, giving every team the speed to act and IT the control to scale. Sigma is trusted by more than 2,000 customers, including AMD, Duolingo, Colgate-Palmolive, and JPMorgan Chase.