Engineering Manager: Data Infrastructure & Experimentation

Amplitude; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Amplitude is seeking 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 role requires a solid data science and statistical foundation, hands-on experimentation experience, and proven leadership of a 10–15 person team building data-intensive products across cloud environments.

Qualifications

• Hands-on experimentation, statistics, or causal inference background.
• Experience leading teams of 10–15 members delivering data-intensive products.
• Building large-scale ingestion and distributed computation systems across cloud and data warehouses.
• Ability to connect statistical innovation with data architecture and customer needs.

Responsibilities

• Lead and grow the team responsible for data ingestion, experiment computation, and stats engine.
• Define the technical and scientific strategy for experimentation across Cloud and warehouse native deployments.
• Partner with data scientists and engineers to turn methods into scalable product capabilities.
• Evolve data and computation architecture to support complex experiment designs and datasets.
• Engage with customers to translate challenges into platform improvements.

Skills

Data science

Experimentation

Statistics

Causal inference

Team leadership

Distributed data systems

Cloud data warehouses

Education

Advanced degree in statistics or related field

Tools

Snowflake

BigQuery

Databricks

Job description

Amplitude is seeking 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 role requires a solid data science and statistical foundation, hands-on experimentation experience, and proven leadership of a 10–15 person team building data-intensive products across cloud environments.