Head of Data Analytics
Asana · San Francisco, CA · Enterprise Technology
About this role
Asana is hiring a staff-level Analytics Engineer in the data engineering function based in San Francisco, CA. The posting calls out experience with SQL, Databricks, Data Analytics, AI Agents. Compensation is listed at $269,000–$316,000 per year.
- Role
- Analytics Engineer
- Function
- data engineering
- Level
- staff
- Track
- Management
- Employment
- Full-time
- Location
- San Francisco, CA
- Department
- Enterprise Technology
More roles at Asana
Job description
from Asana careersYou will lead our global analytics function to ensure Asana's most critical business decisions are grounded in trusted, timely data. As a strategic partner, you will oversee the Marketing, Growth, and Revenue analytics teams — ensuring our Product-Led (PLG) and Sales-Led (SLG) engines operate with maximum efficiency and clear ROI. In an AI-first analytics environment, this role goes beyond traditional analytics leadership: you will define the business logic and metric standards that make self-serve trustworthy, drive adoption of AI-powered analytics tools across Marketing, Growth, and Revenue stakeholders, and shift the team from reactive reporting to proactive decision support.
This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.
What you’ll achieve
- Lead and mentor a global, cross-functional team of analysts across San Francisco, Chicago, and Warsaw, setting a high bar for strategic thinking, executive communication, and AI-augmented ways of working.
- Drive the strategy for analytics, focusing on acquisition efficiency, spend optimization, and comprehensive dashboards for SLG and PLG motions, with AI-powered self-serve at the center of how insights reach stakeholders.