Staff Analytics Engineer

About Topline Pro

We’re building AI powered Shopify for service businesses. We help service pros (e.g., roofers, landscapers, painters, cleaners) acquire direct business, fast. Up and running within minutes using Gen AI, our digital storefront products help pros get discovered, trusted, and booked repeatedly.

Topline Pro is co-founded by Nick Ornitz (CEO) and Shannon Kay (CPO) with an excellent team of 80+ rockstars with plans to expand more in 2025. We serve thousands of local service businesses and were named as one of the 2023 and 2024 top 50 Tech Companies building for SMBs.

We’re YC-backed and well funded with several years of runway, and we’ve experienced rapid growth in the past year. We’re in a phenomenal position to scale—with the financial foundation, product-market fit, and momentum to go big. You’ll be joining at an inflection point—where the groundwork is laid and the path to massive impact is clear.

We believe “great candidates” do not come about through simply a checkmark next to past experiences. We believe in hiring people not just skills. Even if you do not check every box but find excitement at the prospect of working with us in this capacity, please apply.

We’re hiring a Staff Analytics Engineer to take ownership of how data is modeled, organized, and scaled at Topline Pro. You’ll be responsible for building the data assets that sit at the core of our business—turning information from systems like Stripe, Twilio, Dialpad, Salesloft, Hub Spot, and others into clean, trustworthy data models. Your work will give teams across the company confidence in the numbers and the ability to make better, faster decisions.

This is a senior, hands‑on role at the intersection of engineering, analytics, and business strategy. You’ll shape the way data flows through the company and ensure we have the right foundation to measure performance, experiment, and grow.

• Own the centralized data assets that serve as the source of truth for the company’s most important operational questions, including their governance and quality guarantees.
• Design scalable data architectures and well‑modeled dbt/Snowflake layers that stay performant across SaaS‑scale datasets.
• Model Stripe data with precision — payments, subscriptions, revenue, and related financial flows.
• Codify and democratize standards for SQL optimization, query reusability, documentation, testing, monitoring, and code review, driving consistency and efficiency across the team.
• Lead the technical execution of high‑complexity BI and analytics projects in Hex, from design through production.
• Partner with engineering, product, operations, and GTM teams to understand their needs and translate them into high‑impact data solutions.

• 8+ years in analytics engineering, data engineering, or a closely related IC role, with recent depth in modeling for consumption — not just pipeline delivery.
• Fluency in SaaS business metrics (MRR, retention, churn, cohorts, expansion) and the modeling decisions behind them.
• Extensive Snowflake and dbt experience: incremental strategies, testing, macros, semi‑structured data, and an eye on warehouse performance and cost.
• Advanced SQL, including the judgment to spot where a model will silently produce wrong numbers rather than fail loudly.
• Deep fluency in subscription billing and payments data: invoices, proration, refunds, and revenue recognition Finance can close the books on, applied both to company revenue and to how our payments product is performing.
• Track record owning centralized fact and dimension layers the whole company depends on.
• Ability to turn ambiguous business questions into durable models, and to raise the bar around you through code review, documentation, and…