Senior Analytics Engineer

Pantheon Systems, Inc

3d • $135,000 - $225,000 • Onsite

About The Position

The Analytics Engineering team owns how Pantheon's data becomes trusted, self-serve insight — from the data models built on our raw source tables to the semantic layer the whole company consumes. Sitting close to the business (under Finance), you'll own a domain end-to-end and act as a partner who turns business questions into the right data models.

Requirements

• 6–8 years of overall experience in analytics, data engineering, or a related field, including at least 4 years specifically in analytics engineering.
• Advanced SQL and hands-on experience with dbt or a comparable transformation framework (models, tests, documentation)
• Cloud data warehouse experience, ideally Snowflake
• BI / semantic-layer modeling experience, ideally Looker (LookML) or Omni
• Strong dimensional/data-modeling fundamentals (Kimball design, star schema)
• Proven ability to translate business questions into data models — strong business acumen and stakeholder communication
• Comfortable with git and a modern analytics development workflow (branch-based PRs and code review)

Nice To Haves

• SaaS finance fluency — ARR, MRR, NRR (especially valuable given we sit under Finance)
• Depth in GTM/RevOps data (Salesforce) or post-sales/CS data (Zendesk), depending on the domain
• Familiarity with AI- or natural-language-driven analytics
• Exposure to orchestration (Airflow), reverse ETL, or working alongside data engineering
• CI/CD for analytics code (e.g., dbt tests running on PRs via GitHub Actions)

Responsibilities

• Own the analytics modeling lifecycle for a business domain (GTM / Lead-to-Customer or Post-Sales) — build and maintain dbt models and business marts on top of our source data in Snowflake.
• Develop and maintain the semantic layer that powers our BI platform.
• Partner directly with stakeholders across Finance, Sales, Marketing, CS, and RevOps to translate ambiguous business questions into the right model — prescribing or designing one when none exists.
• Define, document, and enforce consistent metric definitions and segmentation across the org (e.g., customer lifecycle stages, production lifecycle, ARR), establishing whether each lives in dbt or the semantic layer so metrics aren't defined twice.
• Build trustworthy self-serve data products so business partners can answer routine questions without help.
• Collaborate with the Data Platform team where raw data is handed off — specify and request new sources, validate data, and raise quality issues upstream.

Benefits

• Industry competitive compensation and equity plan
• Flexible time off, sick days, and 13 paid holidays
• Comprehensive medical insurance including Health, Dental and Vision
• Paid parental leave (plus fertility, adoption and other family planning benefits)
• In-office workspace (San Francisco & Chicago)
• Monthly allowance for wellness, reading and access to LinkedIn Learning for continued development
• Events and activities both team-based and company wide that inspire, educate and cultivate

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed