The RoleAnalytics at Rogo is how we understand our product, our customers, and our business. As an Analytics Engineer, you will be a trusted data partner across the company - embedded with Finance, GTM, Product, and Engineering - building the pipelines, models, and dashboards that turn raw data into decisions.
This is a domain-agnostic role. You will not be siloed into one function. You will work across our entire data ecosystem - from third-party vendor datasets to customer-facing usage reports to GTM performance analytics - and be expected to develop a genuine understanding of how Rogo's business works. The best person in this role won't just answer questions; they'll anticipate them.
We are looking for someone who brings a full-stack mindset, a strong business instinct, and a genuine excitement about using AI to change how this work gets done. If you want to help define what modern analytics looks like at a frontier AI company, we'd love to talk.
What You Will Own- Build, maintain, and extend data pipelines and dbt models that transform raw data into clean, reliable datasets used across the company
- Own the reporting layer across key business domains - building internal tooling and dashboarding to give our teams the visibility they need to make decisions
- Develop a deep familiarity with Rogo's data model and become a go-to resource for stakeholders who need to understand what the data says and what it means
- Support our third-party vendor relationships with financial data providers (LSEG, FactSet, Pitchbook,etc) in close partnership with engineering and our data PM
- Support GTM analytics by building the data layer that powers account health, pipeline reporting, and customer activity tracking - augmenting a strong RevOps team with reliable, well-modeled data
- Build customer-facing analytics and usage reporting - the dashboards and datasets that Rogo's enterprise customers use to understand their own usage, adoption, and ROI
- Partner with Finance on the data infrastructure supporting FP&A, unit economics, and board reporting - ensuring metrics are consistent, trustworthy, and well-documented
- Contribute to a high standard for data quality, testing, and documentation across the analytics codebase
What You Will Need- 4-8 years of experience in analytics, data engineering, or a closely related role
- Deep SQL proficiency - you write and optimize complex queries fluently and know your way around a modern cloud data warehouse (Snowflake preferred)
- Hands-on dbt experience: models, tests, macros, and a sense for what makes a well-structured transformation layer
- Experience building dashboards and reports that non-technical stakeholders actually find useful (Sigma, Looker, Hex, or similar)
- A full-stack mindset - you don't hand off problems at the edge of your job description; you follow them through
- Business instinct - you understand that data work exists to drive decisions, and you connect your output to outcomes, not just deliverables
- Comfort operating across multiple stakeholders and domains without a lot of hand-holding
Bonus- Experience with third-party financial or B2B data vendors (LSEG, FactSet, Crunchbase, ZoomInfo, Apollo, or similar)
- Familiarity with Salesforce data models and GTM data pipelines
- Python proficiency for data transformation or analytical work
- Background in financial services, enterprise SaaS, or vertical AI
- Experience building analytics at an early-stage startup
Who You Are- You thrive in fast-paced environments. You are high-intensity and care a lot about what you do, and you're ecstatic to work at a startup.
- You are ambitious. You have fun solving problems that others think are impossible.
- You are curious. You find joy in learning about AI, technology, and finance.
- You are an owner. You are autonomous, self-directed, and comfortable working with ambiguity.
- You are collaborative, organized, thoughtful, and kind.
