Engineering Manager (Experimentation Data Infrastructure)

Join Amplitude as an Engineering Manager for the Data Infrastructure team within Statsig Experiment. You will lead a multidisciplinary team responsible for data ingestion, computation, and the stats engine. This role requires a strong data science background and experience in building large-scale data systems. You will define the technical and scientific strategy for advancing experimentation and engage with customers to understand their challenges. Benefits include generous parental leave, flexible vacation time, wellness stipends, and equity options.

• Lead and grow a multidisciplinary team responsible for data ingestion, experiment computation, and statistical engine development.
• Define the technical and scientific strategy for advancing experimentation across both Statsig Cloud and warehouse-native deployments.
• Partner with data scientists and engineers to turn new statistical and causal inference methods into scalable, reliable product capabilities.
• We are looking for a leader with a solid data science and statistical foundation who can connect advances in experimentation methodology with scalable production systems
• The ideal candidate is equally comfortable discussing causal inference and statistical power with data scientists, distributed computation architectures with engineers, and experimentation strategy with customers
• Familiarity with experimentation methods such as variance reduction, sequential testing, Bayesian inference, causal effects modeling, or heterogeneous treatment effects
• Experience building large-scale data ingestion and distributed computation systems across cloud and data warehouse environments
• Experience leading teams (10-15 team members) that build and productionize statistically rigorous, data-intensive products
• A strong data science background, with hands-on experience in experimentation, statistics, or causal inference. Experience solely in data engineering is not sufficient for this role
• The ability to connect statistical innovation, data architecture, and customer needs to define a compelling experimentation roadmap
• Experience with experimentation platforms, feature management systems, product analytics, or machine learning infrastructure
• An advanced degree in statistics, mathematics, computer science, economics, or another quantitative field
• Experience building warehouse-native products or executing computation within Snowflake, BigQuery, Databricks, or similar environments
• Experience supporting experimentation for large-scale consumer products, B2B products, marketplaces, social networks, or other settings with complex units of analysis