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Rogo

Analytics Engineer

Reposted 2 Hours Ago
In-Office
New York City, NY, USA
150K-230K Annually
Mid level
In-Office
New York City, NY, USA
150K-230K Annually
Mid level
Build and maintain data pipelines and dbt models, own reporting and dashboards across Finance, GTM, Product, and Engineering, support third-party financial data integrations, enable GTM and customer-facing analytics, and ensure data quality, testing, and documentation.
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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 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.

Why Join Rogo?
  • Up and to the right: Rogo has strong product adoption with the world's leading financial institutions, and we are still early. The upside is enormous.

  • Extraordinary team: we take talent density seriously. You'll do the best work of your career alongside some of the sharpest people in AI and finance.

  • A one-of-one problem: bringing AI to the core of how Wall Street works is one of the most ambitious, technically demanding, and consequential problems today. There is nowhere else you can work on it at this scale.

  • Real ownership: You'll own real surface area and watch the world's most sophisticated users rely on your work.

  • Always at the frontier: we work at the edge of what the best models can do and turn it into products people trust. If you're obsessed with AI, this is where it's happening.

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