Job 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 defines the metrics, runs the pipelines behind them, and turns both into decisions and a better product. We’re hiring a Data Engineer to take full ownership of our Analytics infrastructure and build it into something that scales confidently with the company. This is a hands-on, high-leverage role: pipelines, orchestration, and reliability. If you are an experienced data engineer excited about how your role can evolve at an AI-native organization, this is the opportunity for you. In many ways this is also a product role. Rogo productizes how we use our own data — many of our Analytical features began as internal analytics work. You will be expected to know the product as well as any engineer here, because the systems you build both measure it and support its development. We expect everyone at Rogo to take ownership of making our product better for our users. WHAT YOU WILL OWN - Own analytics infrastructure: the ETL pipelines, Snowflake, dbt models, orchestration, and the reliability of all of it. - Analytics evals: design and run the evaluation and testing layer for our agentic analytics surfaces — internal agents that answer thousands of questions a quarter, and the customer-facing analytics our enterprise admins rely on. This is one of the defining problems of doing analytics at an AI company. - Own core KPIs: the definitions, the pipelines that produce them, and the documentation that makes them legible. When a number moves, you can say whether the pipeline broke, the definition changed, or the business moved. - Know the product inside and out: develop the same depth of product understanding as any engineer or salesperson at Rogo. - Turn internal work into product: partner with engineering and product where our analytics infrastructure becomes a customer-facing feature. - Pick up a lane of analytics work: as the foundation solidifies, take a domain of your own and go deep, so the team’s judgment grows alongside its infrastructure. WHAT YOU WILL NEED - 5+ years of professional experience in data engineering, analytics engineering, or a closely related role, with a track record of owning production data systems. - Deep SQL proficiency and fluency in a modern cloud data warehouse (Snowflake preferred) - Hands-on dbt experience: models, tests, macros, incremental strategies, and a real point of view on what makes a well-structured transformation layer. - Strong Python for pipeline and transformation work, and comfort with orchestration and modern ETL tooling. - You have a real point of view on keeping a fast refresh cadence as event volume geometrically increases with our business: partitioning strategies, incremental model design, storage tiering, etc. - Genuine fluency with AI products. You’ve used agentic tools seriously and have a working picture of what happens between a question and an answer: retrieval, tool calls, model turns, and where cost accrues. - Real curiosity about the business. You care about and take ownership of what a number means, not only that the job ran. - Comfort operating with autonomy across multiple stakeholders and domains. BONUS - Growth-stage experience, or familiarity with the scale of data Rogo will be handling twelve months from now. - Experience building evals or test harnesses for LLM-powered systems. - Experience with single- and multi-tenant customer architectures. - Familiarity with Salesforce, Intercom, or usage-based billing data models (Metronome or similar). - Experience with third-party financial or B2B data vendors (LSEG, FactSet, Crunchbase, ZoomInfo, Apollo, or similar). - Background in financial services, enterprise SaaS, or vertical AI. 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.

Requirements

Must-haves

Own analytics infrastructure: the ETL pipelines, Snowflake, dbt models, orchestration, and the reliability of all of it.
Own core KPIs: the definitions, the pipelines that produce them, and the documentation that makes them legible. When a number moves, you can say whether the pipeline broke, the definition changed, or the business moved.
Know the product inside and out: develop the same depth of product understanding as any engineer or salesperson at Rogo.
Turn internal work into product: partner with engineering and product where our analytics infrastructure becomes a customer-facing feature.
Pick up a lane of analytics work: as the foundation solidifies, take a domain of your own and go deep, so the team’s judgment grows alongside its infrastructure.
5+ years of professional experience in data engineering, analytics engineering, or a closely related role, with a track record of owning production data systems.
Hands-on dbt experience: models, tests, macros, incremental strategies, and a real point of view on what makes a well-structured transformation layer.
Strong Python for pipeline and transformation work, and comfort with orchestration and modern ETL tooling.
You have a real point of view on keeping a fast refresh cadence as event volume geometrically increases with our business: partitioning strategies, incremental model design, storage tiering, etc.
Genuine fluency with AI products. You’ve used agentic tools seriously and have a working picture of what happens between a question and an answer: retrieval, tool calls, model turns, and where cost accrues.
Real curiosity about the business. You care about and take ownership of what a number means, not only that the job ran.
Comfort operating with autonomy across multiple stakeholders and domains.
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.

Nice-to-haves

Deep SQL proficiency and fluency in a modern cloud data warehouse (Snowflake preferred)
Growth-stage experience, or familiarity with the scale of data Rogo will be handling twelve months from now.
Experience building evals or test harnesses for LLM-powered systems.
Experience with single- and multi-tenant customer architectures.
Familiarity with Salesforce, Intercom, or usage-based billing data models (Metronome or similar).
Experience with third-party financial or B2B data vendors (LSEG, FactSet, Crunchbase, ZoomInfo, Apollo, or similar).
Background in financial services, enterprise SaaS, or vertical AI.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigosqlpythonllm

Platform: ashby
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