Senior Analytics Engineer

San Francisco, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Biotechnology, Software, Data & AnalyticsIndustries

Requirements

Candidates must possess expertise in SQL and dbt, proficiency in at least one programming language such as Python, R, or Scala, and experience with cloud data warehouses like Snowflake or Databricks. Strong visualization skills, preferably with Sigma, and experience using git for version control are essential. The role requires comfort with ambiguity in a fast-paced environment, GTM domain expertise, and excellent communication skills to explain complex data insights to non-technical stakeholders. A positive attitude and the ability to provide and receive constructive feedback are also necessary.

Responsibilities

The Senior Analytics Engineer will design, develop, and maintain core data models and create visualizations using Sigma to support Go-To-Market initiatives, ensuring data accuracy and usability. They will partner with stakeholders to understand requirements and deliver scalable data solutions, while clearly scoping, tracking, executing, and communicating on projects. Responsibilities include defining and implementing data engineering standards and best practices, providing guidance to team members, and serving as the in-house expert on sales analytics to enable field insights.

Skills

SQL

dbt

Python

Scala

Snowflake

Databricks

Sigma

Git

Data Modeling

Data Visualization

Sales Analytics

Go-To-Market (GTM)

Data Governance

Version Control

Communication

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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