Job description

ABOUT CODERABBIT CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million code reviews each week. We build the symbiotic partnership between developers and AI that makes shipping fast software safe again, reviewing every pull request, IDE change, and CLI commit so teams can move quickly without breaking things. We are a fast-moving, well-funded company, fresh off a $143M Series C at a $1.5B valuation — building Agentic Change Management, the control layer for software changes created by humans and agents. As AI writes more of the world's code, the bottleneck moves from implementation to judgment and helping human judgment scale is exactly the problem we exist to solve. THE OPPORTUNITY CodeRabbit helps engineering teams trust the code their AI agents write. We want the same confidence in our own numbers. As our Senior Data Analyst, you’ll build the dashboards and reports that give leadership strategic insight across Finance, Revenue, Marketing and Product. You’ll launch our foundational BI tool, then build the agentic workflows that model our data and generate new dashboards and insights on request. You’ll join a small Business Systems team that builds with frontier AI tools every day. KEY RESPONSIBILITIES - Launch our foundational BI tool and build the first exec and team dashboards on it. - Build exec- and board-level reporting for Finance and GTM, including ARR waterfalls, pipeline, funnel and deal risk. - Run deep-dive analyses on the gaps between targets and actuals, pipeline health, margins, and billing issues. - Build and maintain dbt models that form a governed data layer, so people and agents can query with confidence. - Identify gaps in our data warehouse, ETL pipelines, and semantic layer to enforce canonical definitions and shared metrics across the business. - Build and maintain the context layer and agentic harness that let anyone at CodeRabbit generate dashboards and insights on request, with tests and review before anything ships. - Work as a collaborative partner to Finance and GTM: understand their problems and needs, then build workflows and data products that scale with our teams. QUALIFICATIONS - 3+ years as a data analyst or senior data analyst, ideally at a high-growth B2B SaaS company. - Strong SQL and hands-on experience with a cloud data warehouse such as BigQuery or Snowflake. - Experience building and maintaining dbt models and the semantic layer. - Experience building dashboards and self-serve analytics in a modern BI tool such as Omni, Sigma or Looker. - Working knowledge of finance and GTM metrics: ARR, net and gross retention, bookings, pipeline coverage, CAC and gross margin, and how a forecast miss gets traced to its causes. - Real experience using agentic tools such as Claude Code or Codex for analysis and for building, with something you built that you can show us. - Comfortable working with messy data and understanding trade-offs when drawing insights. - Ability to work and communicate with senior leadership, and technical and non-technical peers. PREFERRED QUALIFICATIONS - Familiarity with ETL and ELT pipelines, orchestration tools (such as Airflow, Dagster or Fivetran) and reverse ETL. - Experience at an AI company or early-stage startup, where definitions change and you build the first version of everything. - Experience with CRMs like Salesforce and billing systems like Chargebee - Python or TypeScript, Git and code review, or a dashboards-as-code tool such as Evidence, Streamlit or Observable. - Experience building agent tooling: MCP servers, an agent harness, or CI for analytics code. - Experience with finance reporting, such as an ERP or month-end close, and with usage-based or PLG-to-sales-led pricing, across PLG and SLG motions. Target salary for this role is $170k-$200k, plus equity. Actual salary will be based on candidate skills, experience and location

Requirements

Must-haves

Launch our foundational BI tool and build the first exec and team dashboards on it.
Build exec- and board-level reporting for Finance and GTM, including ARR waterfalls, pipeline, funnel and deal risk.
Run deep-dive analyses on the gaps between targets and actuals, pipeline health, margins, and billing issues.
Build and maintain dbt models that form a governed data layer, so people and agents can query with confidence.
Identify gaps in our data warehouse, ETL pipelines, and semantic layer to enforce canonical definitions and shared metrics across the business.
Build and maintain the context layer and agentic harness that let anyone at CodeRabbit generate dashboards and insights on request, with tests and review before anything ships.
Work as a collaborative partner to Finance and GTM: understand their problems and needs, then build workflows and data products that scale with our teams.
3+ years as a data analyst or senior data analyst, ideally at a high-growth B2B SaaS company.
Strong SQL and hands-on experience with a cloud data warehouse such as BigQuery or Snowflake.
Experience building and maintaining dbt models and the semantic layer.
Experience building dashboards and self-serve analytics in a modern BI tool such as Omni, Sigma or Looker.
Working knowledge of finance and GTM metrics: ARR, net and gross retention, bookings, pipeline coverage, CAC and gross margin, and how a forecast miss gets traced to its causes.
Real experience using agentic tools such as Claude Code or Codex for analysis and for building, with something you built that you can show us.
Comfortable working with messy data and understanding trade-offs when drawing insights.
Ability to work and communicate with senior leadership, and technical and non-technical peers.

Nice-to-haves

Familiarity with ETL and ELT pipelines, orchestration tools (such as Airflow, Dagster or Fivetran) and reverse ETL.
Experience at an AI company or early-stage startup, where definitions change and you build the first version of everything.
Experience with CRMs like Salesforce and billing systems like Chargebee
Python or TypeScript, Git and code review, or a dashboards-as-code tool such as Evidence, Streamlit or Observable.
Experience building agent tooling: MCP servers, an agent harness, or CI for analytics code.
Experience with finance reporting, such as an ERP or month-end close, and with usage-based or PLG-to-sales-led pricing, across PLG and SLG motions.
Target salary for this role is $170k-$200k, plus equity. Actual salary will be based on candidate skills, experience and location

Application prep

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

Keywords to mirror

aisqlpythontypescript

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