Strategy & Execution Manager, GTM

Databricks
San Francisco, with offices around the globe2026-03-20

About the job

The Strategy & Execution Manager is responsible for operationalizing Services and Enablement strategy using AI. You will lead the optimization of programs, financial planning, and cross-functional initiatives to scale the business for continued hyper-growth. This role is unique: you will bridge the gap between high-level executive strategy and technical execution, specifically by leveraging AI automation to streamline Services and Enablement delivery, improve margins, and automate complex internal workflows. The ideal candidate has not just worked with AI tools — they have built end-to-end AI-powered solutions using the modern AI and data stack and brings firsthand experience shipping production-grade systems.

Responsibilities

Strategic Planning & Execution — Support Long Range Planning, OKRs, and identifying risks in planning assumptions for the Services and Enablement organization

AI & Process Automation — Identify inefficiencies within the Services and Enablement lifecycle and build AI agents to address them. You will be hands-on in the build — from prompt engineering and RAG pipelines to agent orchestration and evaluation frameworks

Modern Data Stack Ownership — Architect and maintain the data infrastructure underlying operational dashboards and AI systems, using tools Databricks native stack

Cross-Functional Leadership & Enablement — Act as the connective tissue between Senior Sales, Services, and Enablement Leadership and technical teams

Qualifications

Minimum

7+ years in Strategy, Operations, or Product Leadership, with at least 3 years of hands-on experience building technology solutions or data products in production environments

AI Builder (Required): Demonstrated track record of designing and shipping end-to-end AI solutions. Experience with Foundation Model APIs is strongly preferred

Modern Data Stack Proficiency (Required): Fluency across the modern data stack — including Databricks, Spark, Delta Lake, and cloud data warehouses. Ability to write production-quality SQL and Python

Preferred

Strategic Mindset: Proven ability to interpret complex data sets (e.g., cloud infrastructure costs, market sizing) to derive actionable investment insights

Technical Depth Meets Business Acumen: Comfortable owning a data pipeline and a board-level presentation in the same week

Communication: Ability to present complex AI and data concepts to executive stakeholders in a clear, concise fashion

Proactive Problem-Solving: You don't wait for a tool to exist — you build it

Adaptability & Curiosity: Genuine enthusiasm for staying current with the rapidly evolving AI landscape