AI Data Lead - OurRitual

Own the vision and roadmap for the data function, including the shift from classic BI to agent-based, AI-driven BI Set priorities in partnership with senior leadership Work closely with a data engineer today, with the option to grow the team as the function scales Drive adoption of AI across data workflows — from automating analyses to agents answering business questions in real time Own the semantic and metrics layer so every dashboard and every agent reads the same definitions Build in a git-based workflow: dashboards and queries live in git, edited through PRs, built with agents Expose our data to agents over MCP so business questions get answered without waiting for a dashboard Define where AI speeds things up — and where human judgment still has to hold the line Own the data infrastructure: BigQuery, dbt, pipelines, and data reliability Lead complex analytics work, A/B testing, and impact measurement, hands-on Define evals and quality metrics for AI features and agents — not just A/B tests on dashboards Partner with product, marketing, finance, operations, and engineering to define analytical needs and turn them into solutions Represent the data function to the organization — senior-level storytelling with data 7+ years of experience in data roles, spanning both analytics and infrastructure Strong analytical foundation — you understand what makes analysis rigorous, not just what makes it automatable, and can use that to build an AI-driven analytics system that's actually trustworthy Hands-on experience integrating AI into data workflows — building it, not just using it; you've shipped an agent or AI analysis flow that people actually use Strong SQL skills and experience building scalable data infrastructure Track record owning data projects independently with stakeholders across the business Solid grounding in experimentation and statistical methods Excellent communication and presentation skills at a leadership level Comfortable being the most senior (and often only) data voice in the room Experience with dbt Experience with Amplitude Experience with BigQuery Experience with git-based BI workflows or tools like Modus B2C environment experience

Own the vision and roadmap for the data function, including the shift from classic BI to agent-based, AI-driven BI Set priorities in partnership with senior leadership Work closely with a data engineer today, with the option to grow the team as the function scales Drive adoption of AI across data workflows — from automating analyses to agents answering business questions in real time Own the semantic and metrics layer so every dashboard and every agent reads the same definitions Build in a git-based workflow: dashboards and queries live in git, edited through PRs, built with agents Expose our data to agents over MCP so business questions get answered without waiting for a dashboard Define where AI speeds things up — and where human judgment still has to hold the line Own the data infrastructure: BigQuery, dbt, pipelines, and data reliability Lead complex analytics work, A/B testing, and impact measurement, hands-on Define evals and quality metrics for AI features and agents — not just A/B tests on dashboards Partner with product, marketing, finance, operations, and engineering to define analytical needs and turn them into solutions Represent the data function to the organization — senior-level storytelling with data 7+ years of experience in data roles, spanning both analytics and infrastructure Strong analytical foundation — you understand what makes analysis rigorous, not just what makes it automatable, and can use that to build an AI-driven analytics system that's actually trustworthy Hands-on experience integrating AI into data workflows — building it, not just using it; you've shipped an agent or AI analysis flow that people actually use Strong SQL skills and experience building scalable data infrastructure Track record owning data projects independently with stakeholders across the business Solid grounding in experimentation and statistical methods Excellent communication and presentation skills at a leadership level Comfortable being the most senior (and often only) data voice in the room Experience with dbt Experience with Amplitude Experience with BigQuery Experience with git-based BI workflows or tools like Modus B2C environment experience

Own the vision and roadmap for the data function, including the shift from classic BI to agent-based, AI-driven BI Set priorities in partnership with senior leadership Work closely with a data engineer today, with the option to grow the team as the function scales Drive adoption of AI across data workflows — from automating analyses to agents answering business questions in real time Own the semantic and metrics layer so every dashboard and every agent reads the same definitions Build in a git-based workflow: dashboards and queries live in git, edited through PRs, built with agents Expose our data to agents over MCP so business questions get answered without waiting for a dashboard Define where AI speeds things up — and where human judgment still has to hold the line Own the data infrastructure: BigQuery, dbt, pipelines, and data reliability Lead complex analytics work, A/B testing, and impact measurement, hands-on Define evals and quality metrics for AI features and agents — not just A/B tests on dashboards Partner with product, marketing, finance, operations, and engineering to define analytical needs and turn them into solutions Represent the data function to the organization — senior-level storytelling with data 7+ years of experience in data roles, spanning both analytics and infrastructure Strong analytical foundation — you understand what makes analysis rigorous, not just what makes it automatable, and can use that to build an AI-driven analytics system that's actually trustworthy Hands-on experience integrating AI into data workflows — building it, not just using it; you've shipped an agent or AI analysis flow that people actually use Strong SQL skills and experience building scalable data infrastructure Track record owning data projects independently with stakeholders across the business Solid grounding in experimentation and statistical methods Excellent communication and presentation skills at a leadership level Comfortable being the most senior (and often only) data voice in the room Experience with dbt Experience with Amplitude Experience with BigQuery Experience with git-based BI workflows or tools like Modus B2C environment experience