The opportunity
Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working,…
What you'll do
Lead & Develop: Build, coach, and grow a high-performing team of Analytics Engineers and Data Scientists. Invest in their development, hold a high bar for craft, and create an environment where strong technical people do their best work.
Shape Our Data Culture: Influence the organization to become more metrics-driven — establishing clear KPIs, helping teams define success upfront, and building the operating rhythms that make analytics a strategic partner from the start rather than an afterthought.
Own the Data End to End: Guide the team across the full data lifecycle — ingestion, modeling through our medallion architecture on BigQuery, and production of the trusted tables and reporting artifacts that serve as the company's single source of truth. You'll also help the team apply AI where it strengthens our own product, such as anomaly detection, forecasting, or AI-assisted insight generation, ensuring we're building the capabilities we'd expect any modern data function to have.
Partner & Drive Insight: Serve as the senior data partner to leaders across Product, Engineering, Marketing, Sales, CS, and Finance — surfacing the questions that matter, translating them into analytical approaches, and turning findings into clear recommendations. Hold the team to a standard of insight, not just analysis.
Raise the Technical Bar: Continue elevating standards for pipeline reliability, SQL, dbt practices, data modeling, experimentation, and statistical rigor.
Communicate & Manage Change: Translate company strategy into clear priorities, and guide your team through evolving business needs with clarity.
What they're looking for
- Innovate & Eat Our Own Dog Food: We use Mixpanel to understand Mixpanel. Find new ways to combine our warehouse, product analytics, and experimentation tools to set the example of what data-driven looks like. With a lean team, you'll look for ways AI can extend our capacity, from AI-assisted coding and pipeline development to accelerating analysis, so the team's time goes to judgment and insight, not repetitive work.
- Has progressive experience in data and analytics in a B2B SaaS environment,: including 3+ years of people management — ideally across both Analytics Engineering and Data Science. More senior candidates who've led a centralized data function are also encouraged to apply.
- Is highly effective at driving organizational change: building trust with cross-functional leaders, influencing how teams set and measure goals, and embedding data into how decisions get made.
- Brings strong technical fluency across the full data stack: ingestion and pipeline orchestration, SQL, dbt, data warehouse design (BigQuery, Snowflake, or similar), Python, statistical modeling, experimentation, and forecasting, and experience with AI.
