Staff Analytics Engineer, Topline Pro

• 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 standards
• A failure-modes instinct — anticipates what breaks before shipping, and designs for maintainability over cleverness

Desirable

• 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, HubSpot, 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