Senior Analytics Engineer (Commercial)

• Our commercial strategy is only as strong as the data behind it
• As a member of the Commercial Strategy & Analytics team, you’ll build the data models that power how we measure, understand, and grow our business
• You’ll turn data from our revenue systems into trusted, well-documented models that match how the business defines metrics like ARR, bookings, and pipeline
• You’ll also document how to report on them, so any team pulling its own data gets the same answer
• And you’ll build the models that help us find growth, including upsell and whitespace potential across our account base, ICP fit, and account scoring
• This is a senior, hands-on individual contributor role for someone who leads like an owner
• You’ll set the roadmap, keep our core data current as our revenue systems evolve, and balance speed with long-term quality
• You’ll report directly to the Director of Commercial Strategy & Analytics, on a small team focused on helping commercial leadership make the data-backed calls that drive revenue growth
• Own the function’s roadmap and deliver on it
• Build tested, documented dbt models that match how the business defines ARR, bookings, and pipeline
• Build analytical models for upsell, whitespace, ICP fit, and account scoring
• Build semantic layers that make self-serve easy for analysts and business users
• Build AI-powered tools and automations that make the team faster
• Set the standard for data architecture, QA, and engineering practices (version control, code review, CI/CD, monitoring)
• Own the governance behind our data — clear rules for ownership, access, naming, lineage, and change, grounded in solid data governance practices
• Keep documentation current, including how to report on core metrics so every team gets the same answer
• Partner directly with stakeholders across Sales, Marketing, and Finance to define problems and scope the right solution
• Work with the enterprise data team (hub) and spoke analytics teams on data modeling initiatives. The hub owns ingestion and core infrastructure; you own the commercial modeling layer built on top
• Anticipate future analytics needs and proactively invest in them
• Represent the team in technical planning conversations
• Evaluate and recommend improvements to our data tooling and infrastructure
• Level up analyst’s dbt and modeling skills
• Help build a culture where good data and good decisions go hand in hand

Benefits

• Health and wellness benefits: High quality health plans and access to hormonal and family-building support.
• Time away from work: Generous paid time off including vacation, holidays, sick time, bereavement, and more.
• Financial benefits: Beyond a competitive salary, plans are provided to assist in your financial future including retirement and pension plans as well as life and disability insurance.
• Parental leave: Parents are eligible for time off to care for their newborn, adopted child, or foster child. Parental leave benefits and pay vary by location.
• Professional development: Continuously grow through development workshops, mentoring programs, and more.
• Community impact: We partner with communities to provide services in addition to sponsoring our own events.
• Live your best life: Invest in yourself, on us. Our monthly wellness stipend is designed to support your life beyond the screen, giving you the flexibility to fuel your passions and your well-being.
• Mental health: Access to Headspace’s well known meditation support plus coaching and therapy, for you and additional loved ones.

• Expert-level SQL and solid Python, both second nature for ad-hoc discovery, data workflows, and automation
• Experience building analytical models for GTM teams, such as account scoring, ICP, propensity, or whitespace analysis
• 8+ years in data or analytics roles, with 3+ in analytics engineering, ideally at a fast-paced, data-driven company
• End-to-end ownership of production data models in Snowflake (or a similar enterprise warehouse), including the trade-off calls between completeness, performance, and speed
• Deep, hands-on expertise in data modeling — from raw source data to models people actually want to build on
• A leader’s instinct for ambiguity — you set your own direction, know what good looks like, and build it from scratch
• Experience inheriting, maintaining, and improving data models and ETL/ELT pipelines built by other people, adapting comfortably to different styles and existing constraints
• The instinct to break big projects into clean, well-scoped pieces, while juggling conflicting priorities
• Genuine curiosity about the business behind the data — you’ll pick up our booking definitions, sales motions, and product portfolio quickly, because the right model starts with the right question
• Fluency with our stack — Fivetran, dbt, and Snowflake — and experience building semantic layers, whether in dbt or Snowflake’s semantic tables
• Excellent communication — you can translate a business question into a data model without losing anyone along the way
• Experience applying software engineering practices to analytics: Git, code review, CI/CD, and automated testing