Data Engineer - Tech Operations at Sigma Computing

San Francisco, California, United States

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

SoftwareIndustries

Requirements

Candidates must have at least 3 years of experience in a Data Engineering role, with strong experience working with APIs and building pipelines in cloud platforms like Snowflake and Databricks. Expertise in SQL and dbt, along with fluency in at least one programming language such as Python, R, or Scala, is required. Experience implementing scalable data governance frameworks and startup experience are also necessary qualifications.

Responsibilities

The Data Engineer will design, build, and maintain core data models and visualizations in Sigma to support Engineering and Tech Operations initiatives, ensuring data accuracy and usability. They will architect and manage production data pipelines in Snowflake and their consumption in Sigma, build foundational data assets for Tech Operations including support insights and internal telemetry, and create observability datasets from cloud infrastructure platforms. The role involves partnering with the infrastructure engineering team for data asset availability, building internal data products for self-service usage, and identifying and executing high-impact data projects independently. Collaboration across Engineering, Product, and GTM teams is also a key responsibility.

Skills

Snowflake

Databricks

SQL

dbt

Python

Data Modeling

Data Pipelines

Data Governance

APIs

AWS

GCP

Azure

Fivetran

Metaplane

Hightouch

Sigma Computing

Cloud-based data analytics platform for businesses

About Sigma Computing

Sigma Computing offers a cloud-based data analytics platform that enables businesses to analyze large volumes of data through a user-friendly, spreadsheet-like interface. Users can connect to their cloud data warehouse and access advanced features such as data collection, territory management, and revenue planning without needing coding skills. The platform is scalable, allowing for the analysis of billions of rows of data, and promotes self-service capabilities for faster insights. Recently, Sigma introduced AI features like data classification and natural language processing to enhance data analysis and support Enterprise AI initiatives.

San Francisco, CaliforniaHeadquarters

2014Year Founded

$550.9MTotal Funding

SERIES_DCompany Stage

Data & Analytics, AI & Machine LearningIndustries

501-1,000Employees

Benefits

Competitive pay - Looking for a great salary and solid stock options? You’ve come to the right place.

Flexible schedule - Do the work you need to get done in the time you have to get it done

Amazing benefits - Medical, dental, vision, 401k, FSA, commuter… we’ve got you covered. Literally.

Flexible vacation - At Sigma, we work to live, not live to work. So go on, book that dream vacation.

Health & wellness - A healthy body supports a healthy mind, so we partner with Crunch Fitness and CorePower.

Family-friendly - From flexible scheduling to parental leave to kids’ birthdays off, we support Sigma families.

Risks

Competition from Tableau and Power BI could threaten Sigma's market share.

Reliance on platforms like Snowflake may impact service delivery if disruptions occur.

High valuation pressures Sigma to deliver rapid growth, risking strategic misalignment.

Differentiation

Sigma offers a spreadsheet-like interface for non-technical users to analyze data.

The platform integrates with major data warehouses like Snowflake and BigQuery.

Sigma's AI features include natural language processing and sentiment analysis.

Upsides

Sigma raised $200M in Series D funding, valuing it at $1.5 billion.

The platform's scalability allows analysis of billions of data rows efficiently.

Sigma's partnerships enhance data accessibility and integration for users.

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