The opportunity
The Internal Product Analytics (IPA) team is the analytics backbone of Datadog's Product organization. With over thirty products on a single platform, IPA gives PMs and leadership the data, tooling, platform, and analysis they need to make good decisions.
What you'll do
Guide and grow the Internal Product Analytics team. Manage, coach, and: develop a team of data analysts. Set priorities, hold a high bar for quality, and make sure the team's output is trusted across the Product org.
Partner directly with the PM org. Work side by side with the PMs your team: serves to frame the questions that matter, shape the analysis, and make sure the answers reach them in a form they can act on.
Own the recurring analytics the PM org runs on. Business reviews, feature: request analysis, usage and adoption tracking, and pricing analysis. Make this work consistent, repeatable, and fast so PMs get answers when they need them.
Build AI-first analytics. Design and ship AI-powered workflows and agents: that do the heavy lifting of analysis, from data querying to synthesis to reporting. Set the standard for how the team uses AI so analysis scales without simply adding headcount.
Partner across functions. Work with Finance, Data Platform, Engineering, and: Revenue teams to align on definitions, source the right data, and turn raw signals into decisions. Build trust with partners who do not report to you.
Turn data into decisions for leadership. Query product, CRM, and financial: data to surface the insights that matter, then present them clearly to PMs and senior leadership so they can act with confidence.
What they're looking for
- Set the standard for product analytics across the org. Define the metrics,: definitions, and analytical frameworks that leadership and every PM rely on, and own them as the single source of truth the Product org trusts.
- + years in product analytics, data analytics, or a related field, with 2+ years managing or leading a team.
- A strong track record partnering across functions (Product, Finance,: Engineering, Data) and aligning stakeholders with different priorities toward shared outcomes.
- Proven ability to partner directly with product managers as their analytics: partner, turning product questions into analysis that informs decisions.
