Senior Analytics Engineer

About the Role

We are looking for a builder who speaks the language of business. We need a Senior Analytics Engineer to own the data architecture and modeling that powers our Finance, RevOps, and Executive decision-making.

In this role, you will sit at the intersection of Data Engineering and Business Intelligence. You won’t just be moving data from point A to point B; you will be responsible for designing the "logic layer" of our business. You will work directly with stakeholders to understand business problems and engineer the systems that make that data accurate, accessible, and reliable. You understand that a "churn" metric isn't just a number; it's a specific business definition that needs to be modeled accurately and exposed seamlessly in internal customer facing BI tools like Sigma for stakeholders.

As a Senior Analytics Engineer you will be responsible for…

Data Modeling & Systems Design

• Own the design and maintenance of our Data Warehouse.
• Build clean, performant, and reliable data models (using SQL and dbt) that serve as the "single source of truth" for the company.
• Design the data architecture specifically for high-stakes domains: Finance and Revenue Operations. You will ensure that the numbers reported to the board match the numbers in our BI tools.

ETL & Pipeline Management

• Manage and optimize data pipelines (ETL/ELT) to ingest data from business and product applications into our warehouse.
• Debug data failures and implement automated testing to catch data quality issues before they reach the dashboard.

The "Business-to-Data" Translation

• Act as the technical partner to the Finance and RevOps teams. You will attend their meetings, understand their strategic goals, and translate their requirements into technical specifications.
• Proactively identify gaps in our data collection strategies and work with Engineering/Product to ensure we are capturing the right data upstream.

You will thrive in this role if...

• You are a hybrid: You might have started as a Data Analyst and grew tired of messy data, so you learned engineering. Or, you are a Data Engineer who cares more about how the data is used than the infrastructure it runs on.
• You are a "Full-Stack" Analyst: You are comfortable writing complex SQL, but you also understand software engineering principles like version control, CI/CD, and reusable code.
• You value context: You don’t just write a query; you ask, "Why are we measuring this?" and "How does this definition of 'Active User' impact our revenue reporting?"
• You are a distinct communicator: You can explain a schema change to a Head of Finance and a business metric to a Backend Engineer.

Requirements

• 5+ Years of experience: You have gotten your hands dirty working with engineering and GTM teams solving real cross functional data problems.
• Advanced SQL: You can write complex, highly optimized SQL queries and are comfortable with window functions, CTEs, and query tuning.
• Pipeline Tools: Experience with modern transformation tools (specifically dbt) and ingestion tools.
• Scripting Language knowledge: Proficiency in Javascript / Python for scripting, automation and systems building.
• Business Acumen: Experience working with corporate data (CRM, ERP, Billing systems) is highly preferred. You understand the difference between "Bookings" and "Revenue."
• Cloud Native: You are familiar with the Google Cloud or other cloud ecosystems and understand how to use the systems available to you to solve problems.

The items above are a starting point for a conversation, not a hard list of requirements. If this role excites you, we hope you will apply!

The base salary range for this role is $170,000 - $190,000 USD. This role is also eligible for meaningful company equity and benefits.
This position is fully remote and open to candidates in multiple locations. Compensation may vary by country and local market and will be discussed early in the interview process. Final offer amounts are determined based on experience, role-related knowledge, skills, and abilities.