Analytics Engineer
Rogo
| Company | Rogo |
| Category | Engineering |
| Location | New York |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 25 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
Why Rogo
Our mission is to transform global finance by empowering professionals at the world's top investment banks, private equity funds, and investment firms with AI that delivers unparalleled speed, accuracy, and insight. We're not just improving financial workflows; we're redefining them.
This is a unique opportunity to join a generational company driving transformation in one of the most important industries in the world. With a rapidly growing, global client base, proven product-market fit, and backing from world-class investors, we are scaling quickly and defining a new category of enterprise AI.
Our team is sharp, motivated, and deeply committed to Rogo’s mission. We take ownership of complex problems and stay relentlessly focused on our users. If you thrive in a fast-paced environment, demand excellence, and want to help build the future of finance, we invite you to join us.
THE ROLE
Analytics 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
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