Engineering Manager, Data Infrastructure & Experimentation

Amplitude; San Mateo (CA); Hybrid; USD 254,000 - 381,000; Full time

Benefits offered by this job

Equity

Comprehensive benefits

401(k) with company match

Flexible time off

Parental leave

Wellness programs

Job summary

Amplitude is seeking an Engineering Manager to lead the Data Infrastructure team within the Statsig Experiment group. You will guide data ingestion, computation, and the stats engine, partnering with data scientists and engineers to scale experimentation.

You’ll drive the technical and scientific direction, translating new statistical methods into reliable production capabilities. This role emphasizes leadership alongside hands-on data science and causal inference expertise.

Qualifications

• Strong data science background with hands-on experimentation, statistics, or causal inference.
• Experience leading teams (10-15) delivering data-intensive products.
• Experience building large-scale data ingestion and distributed computation systems.
• Ability to translate statistical methods into production-ready capabilities.
• Familiarity with warehouse-native deployments (Snowflake, BigQuery, Databricks).

Responsibilities

• Lead and grow the Data Infrastructure team across ingestion, computation, and stats engine.
• Define and execute the experimentation strategy for Cloud and warehouse deployments.
• Partner with data scientists and engineers to ship scalable features.
• Evolve architecture to support complex experiments and datasets.
• Engage with customers to translate challenges into platform improvements.

Skills

Data science background

Experimentation/statistics

Causal inference

Team leadership (10-15)

Distributed systems

Cloud data warehousing

Statistical methods

Education

Advanced degree in statistics or CS

Tools

Snowflake

BigQuery

Databricks

OpenTelemetry

Job description

Amplitude is seeking an Engineering Manager to lead the Data Infrastructure team within the Statsig Experiment group. You will guide data ingestion, computation, and the stats engine, partnering with data scientists and engineers to scale experimentation.

You’ll drive the technical and scientific direction, translating new statistical methods into reliable production capabilities. This role emphasizes leadership alongside hands-on data science and causal inference expertise.