Manager, Data & Analytics, In-Store
Listed on 2026-07-24
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IT/Tech
Data Engineering, Data Analyst, Data Science Manager, Business Systems & Technology Analysis
About the Team
The Seven Rooms Data & Analytics team is the foundational data hub for the Seven Rooms business — owning the pipelines, models, dashboards, and predictive systems that power decisions across GTM, Product, Finance, and Partnerships. We sit at the intersection of Seven Rooms and the broader Door Dash data ecosystem, and we partner globally with teams across the US, UK, UAE, and Australia supporting all customer segments from SMB through Enterprise.
We design and maintain the pipelines, models, and infrastructure that connect Seven Rooms' systems with the broader Door Dash data ecosystem — and we're investing aggressively in making our datasets ready for both human and AI consumption.
We're hiring a Manager of Data & Analytics to lead the Seven Rooms D&A team — a team of six (and growing to eight) analysts and engineers responsible for the data products, AI systems, and reporting infrastructure that the rest of the business runs on. You will be both a people leader and a senior technical voice in the room: coaching analysts and engineers on their craft, owning the data roadmap end-to-end, partnering with executive stakeholders across geographies and segments, and rolling up your sleeves on the highest-complexity work.
In your first 90 days, you will absorb the team's in-flight roadmap, build trust with stakeholders across S&O, GTM, Product, Finance, and Partnerships, and partner with leadership on the prioritization framework that governs what the team takes on next. Our 2026 roadmap spans the full data value chain:
GenAI agents that audit Salesforce in real time, churn and ICP models that drive CSM and AE prioritization, the MRR/ARPV reporting layer that finance and leadership run the business on, and the Netsuite integration that will modernize how we report revenue.
You will report into the Senior Manager, Strategy & Operations in our In-Store organization.
You’re excited about this opportunity because you will…- Lead, coach, and grow a team of senior analysts and BI engineers — running performance, career development, and hiring end-to-end.
- Own the D&A roadmap across GTM, Product, Finance, and Partnerships, balancing the team's investment between predictive AI/ML systems, traditional reporting, and cross-functional analytics.
- Act as the senior data voice in executive conversations — translating business problems into technical scope, pushing back when a request is the wrong shape, and influencing how leaders across segments make decisions.
- Translate narrow, well-defined GTM problems into shipped solutions — designing prompts, integrating with Salesforce and our GTM stack via APIs, and instrumenting the leading indicators that prove ROI.
- Partner closely with GTM Engineering, GTM Systems, and Revenue Insights to define a clean "Build vs. Run" operating model and unlock the next generation of AI-powered GTM products.
- Contribute to the team-wide AI developer infrastructure (skills libraries, MCP integrations, prompt frameworks) that makes every D&A engineer and analyst faster at deploying AI.
- Help establish the technical patterns and reusable components that will power our next generation of GTM AI products as the function scales.
- 6+ years of experience in data analytics, BI engineering, or analytics engineering in a B2B SaaS environment, with demonstrated technical depth in SQL, DBT, and a modern cloud data warehouse (Snowflake or Big Query).
- 2+ years of people management experience leading a team of analysts, engineers, or a hybrid of both — including hiring, performance management, and career development.
- Hands‑on experience owning enterprise data infrastructure (Looker or equivalent BI tooling, DBT modeling at scale, Salesforce‑to‑warehouse pipelines) and the judgment to know when to invest in foundations versus ship for speed.
- Proven track record of partnering with executive stakeholders across functions — translating ambiguous business problems into scoped technical work, and pushing back constructively when scope or data readiness is the real blocker.
- Working fluency with modern AI and ML approaches (predictive modeling, LLM‑powered…
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