Sigma Computing

Senior Analytics Engineer - Engineering

San Francisco, California, United States

Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Biotechnology, SoftwareIndustries

Senior Analytics Engineer

Employment Type:

Location Type:

Salary:


Position Overview

With 3.5x growth in ARR and a maturing operating model, Sigma is looking for a curious and collaborative Senior Analytics Engineer to support our Engineering and Technical Support teams. In this role, you’ll enable data-driven decision-making through robust data modeling, reporting, and infrastructure development. You’ll partner closely with Technical Support and Engineering teams to improve operational efficiency, enhance customer insights, and build scalable data solutions for engineering operations.

We welcome candidates from a variety of backgrounds and experiences—even if you don’t meet every listed requirement, we encourage you to apply. If you’re excited about analytics engineering and want to make an impact at a high-growth company, let’s chat!


Responsibilities

  • Design, build, and maintain core data models to power critical Technical Support and Engineering workflows including system performance metrics, incident response data, customer support interactions, and operational telemetry.
  • Model incident tracking data to improve response times for critical outages and system issues while measuring the effectiveness of process improvements and operational changes.
  • Identify opportunities to develop new self-service and data apps tools that streamline engineering operations and support team workflows.
  • Create comprehensive documentation for data models, pipelines, and workbooks to enable self-service data discovery and maximize user adoption across teams.
  • Analyze support request patterns and complexity trends to inform capacity planning and identify opportunities for process optimization as customer needs evolve.
  • Partner closely with Engineering and Technical Support stakeholders to gather requirements and translate them into scalable data products that enhance decision-making, operational visibility, and team efficiency.
  • Mentor team members and cross-functional partners on analytics best practices while establishing and maintaining data quality standards across all deliverables.
  • Drive continuous improvement initiatives by analyzing workflow inefficiencies and recommending data-driven solutions that reduce manual processes and improve team productivity.
  • Deliver reporting and dashboards in Sigma to enable real-time insights into system performance, customer health metrics, and operational KPIs for leadership decision-making.

Qualifications We Need

  • 4+ years of experience in analytics engineering or equivalent role, with experience supporting technical teams.
  • Strong proficiency in SQL (dbt experience preferred) with a deep understanding of dimensional modeling and transformation design for engineering and support use cases.
  • Experience working with engineering and support systems (e.g., Jira, Intercom, ZenDesk, CI/CD Platforms, etc.).
  • Strong grasp of cloud data warehouses (Snowflake or Databricks preferred) and data version control (git).
  • Demonstrated experience supporting Engineering and / or Technical Support stakeholders at a B2B SaaS company (Bonus: experience in other high-growth environments is also valued).
  • Experience with data visualization tools (Sigma experience preferred - you will use Sigma every day!).
  • Excellent communication skills, especially in explaining complex data concepts to technical and non-technical stakeholders.
  • Self-starter with high attention to detail and the ability to manage multiple priorities in a fast-paced environment.
  • Proven ability to influence cross-functional stakeholders and drive adoption of data solutions across technical and business teams.

Bonus Points

  • Prior experience with customer sentiment analysis using natural language processing (NLP) techniques on unstructured data such as chat transcripts.
  • Experience building robust data pipelines and predictive models.
  • Exposure to optimization strategies to improve run-time performance of data models built on high-volume telemetry data.
  • Familiarity with data quality and

Application Instructions

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Company Information

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Skills

Data Modeling
Reporting
Infrastructure Development
Data Pipelines
SQL
Analytics Engineering
Documentation
Capacity Planning
Process Optimization
Stakeholder Management
Mentoring

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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