Business Intelligence Engineer (GTM), In-Store Data & Analytics

DoorDash USA•New York, NY

17d•$98,600 - $145,000•Remote

About The Position

The SevenRooms Data & Analytics team is the foundational data hub powering go-to-market, product, finance, and operational decisions across the In-Store business. We design and maintain the pipelines, models, and infrastructure that connect SevenRooms' systems with the broader DoorDash data ecosystem — and we're investing aggressively in making our datasets ready for both human and AI consumption. Within the team, BI GTM Engineers focus on building the "Build" function on top of our existing GTM Systems "Run" infrastructure - a dedicated capability for engineering AI-powered internal products that eliminate friction across our Pre-Sales and Post-Sales organizations. We ship production AI systems that move our three north star metrics: Locations Signed, Total ARR, and Net Revenue Retention. We're hiring a BI GTM Engineer to help build the AI-powered workflows and proprietary internal tools that help SevenRooms' Pre-Sales and Post-Sales team spend more time selling and less time on administrative work. You will design, build, and ship production GenAI agents and automations on top of Salesforce, Gainsight, Outreach, Gong, and our Google Cloud infrastructure — turning narrow, well-defined GTM problems into production systems within weeks, not quarters. In your first 90 days, you will pair with our Senior GTM Engineer to ship two to three high-leverage AI workflows from the prioritized backlog (examples: automated pre-call research, deal intelligence summaries, P&P Wizard automation), while contributing to our shared AI developer infrastructure that makes the entire D&A team faster. You will report into the Manager, Data & Analytics on our Data & Analytics team in our In-Store organization.

Requirements

2+ years of experience building production software, data, or AI systems - ideally inside a GTM, RevOps, or analytics engineering function at a B2B SaaS company.
Hands-on experience deploying LLM-powered applications in production, including prompt engineering, evaluation, and the integration patterns required to ground models in business data.
Familiarity with modern data stack tooling - particularly DBT and Fivetran - and an understanding of how clean, well-modeled data enables reliable AI outputs.
Strong proficiency in Python and SQL, with working knowledge of REST APIs and Salesforce APIs (SFDC), comfort with GCP (BigQuery, Cloud Functions, Compute Engine, Secret Manager), and experience with infrastructure-as-code tooling such as Terraform.
Demonstrated ability to scope an ambiguous business problem, ship a working v1 quickly, and iterate based on user feedback - not just deliver requirements as written.
Comfortable operating in environments where you’re the builder but not always the one defining what to build - able to extract requirements from non-technical SMEs across Sales, CS, RevOps, and Finance, scope work collaboratively, and drive projects to completion.
Strong written and verbal communication skills, including the ability to partner directly with non-technical GTM stakeholders and translate business problems into technical scopes.
Ambitious and biased toward action - you thrive in fast-moving environments, prefer shipping over speccing, and are energized by seeing your work in the hands of real users.

Responsibilities

Build and ship production AI agents and automations on Google Cloud Platform (BigQuery, Cloud Functions, Compute Engine, Secret Manager, Terraform, VertexAI) that directly touch the daily workflow of every AE, AM, and CSM at SevenRooms.
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 with frontline reps and CSMs as design partners — co-designing solutions, iterating in production, and driving real adoption rather than dashboards nobody opens.
Collaborate cross-functionally with Revenue Operation), Strategy & Operations, Product, Enablement, Customer Success, Sales, and FP&A to surface the right problems and build solutions that stick.
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.