Engineering Manager (Experimentation Data Infrastructure)

Навыки

• B2B-продажи
• BigQuery
• Databricks
• DWH
• Jaeger / OpenTelemetry
• Обучаемость
• Machine Learning

О компании и продукте

• 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: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses.
• Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results.

Задачи

• 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
• You’ll Be a Great Addition to the Team If You Have
• 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
• Particularly Valuable Experience
• 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

Требования

• A strong data science background, with hands-on experience in experimentation, statistics, or causal inference

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