Manager, Sales Strategy & Operations

DoorDash DoorDash · Consumer · San Francisco, CA · 536 Sales S&O

This role is for a Manager of Sales Strategy & Operations at DoorDash. While the company uses AI tools and the role mentions "architect AI-driven solutions" and "build in AI tooling", the core function is sales strategy and operations, not directly building or researching AI models. The role focuses on developing strategic plans, enhancing sales productivity using data tools like SQL, and driving operational excellence. The AI aspects appear to be about leveraging existing AI tools to improve sales processes rather than core AI development.

What you'd actually do

  1. Develop strategic plans in retaining and growing partnerships at scale
  2. Leverage data tools (e.g. SQL) to help enhance sales productivity in targeting and closing the most valuable partnerships
  3. Contribute to post-sales strategy for our top company priorities
  4. Drive operational excellence in reporting cadences, rigorous pipeline tracking, and sales productivity – leading end-to-end ideation to execution through data-driven insights
  5. Partner with our cross-functional teams to expand and elevate our offering

Skills

Required

  • 6+ years of experience in consulting, strategy, business development, operations, technology, banking, analytics or related experience with a track record of leading initiatives and hitting goals
  • strong cross functional business experience, project management, and communication skills
  • comfortable working with large data sets + modeling in Excel / Google Sheets
  • advanced proficiency in SQL
  • well-versed in data visualization tools (e.g. Sigma, Tableau) to help solve ambiguous problems
  • willing to roll up their sleeves and flex up or down as needed - “humble doer”
  • Bachelor’s degree or higher
  • map complex operational workflows, diagnose data gaps, and architect AI-driven solutions end-to-end—from process discovery through prototype to production deployment
  • build in AI tooling (e.g., Claude, ChatGPT, etc.) and ship real automation that eliminates manual work, closes visibility gaps, and accelerates decision-making across the business
  • think in systems, not features
  • treat every broken process as a build opportunity and every data gap as a use case waiting to be deployed

What the JD emphasized

  • architect AI-driven solutions end-to-end—from process discovery through prototype to production deployment
  • build in AI tooling (e.g., Claude, ChatGPT, etc.) and ship real automation that eliminates manual work, closes visibility gaps, and accelerates decision-making across the business
  • This is not an AI-curious role; this is an AI-native operating environment where you are expected to build, test, and iterate continuously