Senior Analytics Engineer (Commercial)

Optro; United States; On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Health benefits

Generous PTO

Retirement plans

Parental leave

Professional development

Wellness stipend

Mental health support

Job summary

Optro is seeking a senior analytics engineering professional to lead and own the data modeling layer that powers revenue metrics such as ARR, bookings, and pipeline. You will design and implement dbt models and semantic layers built on Snowflake, enabling trusted analytics and self-serve insights for sales, marketing, and finance.

You will partner with stakeholders to define problems, maintain governance, and advance AI-powered tools to accelerate data-driven decision making across the

Qualifications

• Expert-level SQL and Python for ad-hoc discovery, data workflows, and automation.
• End-to-end ownership of production data models in Snowflake.
• Fluency with Fivetran, dbt, and Snowflake and building semantic layers.

Responsibilities

• Own the function’s roadmap and deliver on it.
• Build tested, documented dbt models that match ARR, bookings, and pipeline.
• Build analytical models for upsell, whitespace, ICP fit, and account scoring.
• Build semantic layers for self-serve analytics.
• Develop AI-powered tools and automations to speed the team.
• Maintain data governance, version control, CI/CD, and testing practices.

Skills

SQL

Python

Data modeling

Snowflake

dbt

ETL/ELT

Analytics engineering

Communication

Tools

Fivetran

Job description

• 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 automationExperience building analytical models for GTM teams, such as account scoring, ICP, propensity, or whitespace analysis8+ years in data or analytics roles, with 3+ in analytics engineering, ideally at a fast‑paced, data‑driven companyEnd‑to‑end ownership of production data models in Snowflake (or a similar enterprise warehouse), including the trade‑off calls between completeness, performance, and speedDeep, hands‑on expertise in data modeling — from raw source data to models people actually want to build onA leader’s instinct for ambiguity — you set your own direction, know what good looks like, and build it from scratchExperience inheriting, maintaining, and improving data models and ETL/ELT pipelines built by other people, adapting comfortably to different styles and existing constraintsThe instinct to break big projects into clean, well‑scoped pieces, while juggling conflicting prioritiesGenuine 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 questionFluency with our stack — Fivetran, dbt, and Snowflake — and experience building semantic layers, whether in dbt or Snowflake’s semantic tablesExcellent communication — you can translate a business question into a data model without losing anyone along the wayExperience applying software engineering practices to analytics: Git, code review, CI/CD, and automated testing