Engineering Manager (Experimentation Data Infrastructure)

Amplitude•San Francisco, CA

1d•$227,000 - $381,000•Hybrid

About The Position

We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion, Data computation, and Stats engine. This is not a traditional data engineering management role. 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. You will help set our technical and scientific direction, translating new statistical methods and machine learning research into capabilities that customers can use reliably at scale. You’ll partner closely with data scientists, engineers, product managers, and customers to advance the state of experimentation. 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.

Requirements

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.
Experience leading teams (10-15 team members) that build and productionize statistically rigorous, data-intensive products.
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.
The ability to connect statistical innovation, data architecture, and customer needs to define a compelling experimentation roadmap.

Nice To Haves

An advanced degree in statistics, mathematics, computer science, economics, or another quantitative field.
Experience with experimentation platforms, feature management systems, product analytics, or machine learning infrastructure.
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.

Responsibilities

Lead and grow the team responsible for Statsig’s data ingestion, experiment computation, and stats engine.
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.
Evolve our data and computation architecture to support increasingly complex experiment designs, metrics, and customer datasets.
Engage with customers to understand their experimentation challenges and translate them into platform and methodology improvements.