Staff Engineer – Experimentation Team

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Build the experimentation statistical engine — hypothesis testing, sequential analysis, variance reduction (CUPED, Winsorization), power analysis. Ensure statistical correctness across all experiment types.

Design warehouse-native experimentation that runs analysis inside customer warehouses (Snowflake, Databricks, Redshift, BigQuery). Build modular, warehouse-agnostic abstractions for rapid new backend support.

Lead adaptive experimentation — contextual bandit systems, Bayesian optimization, automated allocation beyond simple A/B tests.

Drive the platform roadmap with product, design, and data science. Shape what we build, not just how.

Collaborate cross-functionally with Warehouse Integrations, SDK, Platform, and Data Science teams.

Mentor engineers and raise the team's bar for statistical rigor and system design.
Own operational excellence — monitoring, observability, incident response, on-call. Robust telemetry and alerting.

10+ years building large-scale experimentation platforms, statistical analysis systems, or data-intensive backend services.

Applied-statistics knowledge: hypothesis testing, sequential analysis, variance reduction (CUPED), power analysis, experiment design. Comfortable with frequentist vs. Bayesian trade-offs.

Experience with adaptive experimentation ML — contextual bandits, Thompson sampling, Bayesian optimization, or RL-based allocation.

Track record designing warehouse-agnostic systems across Snowflake, Databricks, Redshift, BigQuery, or similar.

Expertise in Go, Python, or similar for backend services and statistical computation.

Experience with event-driven architectures, data pipelines, and large-scale data processing.

Technical leadership: setting direction, breaking down complex problems, influencing across teams.

Ability to translate statistical concepts for product and engineering audiences.

Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $214,800 - $295,350*
Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $193,400 - $265,870**
Zone 3: All other US locations - $182,600 - $251,0202**

Improving the velocity and stability of software releases, without the fear of end customer outages
Delivering targeted experiences by easily personalizing features to customer cohorts
Maximizing the business impact of every feature through the ability to experiment and optimize
Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types
Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability

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