Data Engineer - Tech Operations, Mid-Level

Qualifications

• Strong experience working with APIs and building pipelines in cloud platforms (e.g., Snowflake, Databricks)
• Expertise in SQL and dbt; fluency in at least one programming language (e.g., Python, R, Scala)
• Experience implementing data governance frameworks that scale
• 3+ years of experience in a Data Engineering role
• Startup experience

Responsibilities

• They are seeking a Data Engineer within Tech Operations to build and optimize data models and pipelines, ensuring high data accuracy and usability for critical insights across the organization
• Design, build, and maintain core data models and visualizations in Sigma to support Engineering & Tech Operations initiatives, ensuring high data accuracy and usability
• Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma (Tech we use: Fivetran, dbt, Snowflake, Sigma, Hightouch, Metaplane)
• Build foundational data assets for Tech Operations, including Support insights and internal telemetry
• Create observability datasets from Sigma’s cloud infrastructure platforms (AWS, GCP, Azure)
• Partner with our infrastructure engineering team to ensure high availability of all key data assets
• Build internal data products and enable self-service usage across Tech Operations
• Identify and execute high-impact data projects in ambiguous environments, working independently to define scope, set priorities, and deliver quickly
• Collaborate across Engineering, Product, and GTM teams to deliver on all of the above

Full Description

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Job Summary:

Sigma is a cloud analytics and business intelligence tool that empowers business teams to explore data and make informed decisions. They are seeking a Data Engineer within Tech Operations to build and optimize data models and pipelines, ensuring high data accuracy and usability for critical insights across the organization.

Responsibilities:

• Design, build, and maintain core data models and visualizations in Sigma to support Engineering & Tech Operations initiatives, ensuring high data accuracy and usability.

• Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma (Tech we use: Fivetran, dbt, Snowflake, Sigma, Hightouch, Metaplane).

• Build foundational data assets for Tech Operations, including Support insights and internal telemetry.

• Create observability datasets from Sigma’s cloud infrastructure platforms (AWS, GCP, Azure).

• Partner with our infrastructure engineering team to ensure high availability of all key data assets.

• Build internal data products and enable self-service usage across Tech Operations.

• Identify and execute high-impact data projects in ambiguous environments, working independently to define scope, set priorities, and deliver quickly.

• Collaborate across Engineering, Product, and GTM teams to deliver on all of the above.

Qualifications:

Required:

• Strong experience working with APIs and building pipelines in cloud platforms (e.g., Snowflake, Databricks)

• Expertise in SQL and dbt; fluency in at least one programming language (e.g., Python, R, Scala)

• Experience implementing data governance frameworks that scale

• 3+ years of experience in a Data Engineering role

• Startup experience

Preferred:

• A drive to continuously learn (and share those learnings) about the evolving data ecosystem

• Experience with modern orchestrators (e.g., Astronomer, Airflow, Dagster)

• Experience building scalable ML systems such as recommendation engines, search or machine translation

Company:

Sigma is not another Business Intelligence tool. Founded in 2014, the company is headquartered in San Francisco, California, USA, with a team of 501-1000 employees. The company is currently Late Stage. Sigma has a track record of offering H1B sponsorships.