Data Engineering Manager, Product

5+ years of experience managing analytics engineering or data engineering teams, preferably in a scaling startup environment

8+ years of total experience in analytics engineering, data engineering, or similar data-focused roles

Deep expertise in data modeling, ETL pipelines, and data warehouse architecture

Strong technical foundation with expertise in SQL, Python, dbt, and modern data stack tools

Proven track record of building and leading high-performing teams

Experience partnering with Data Science, Product, and Engineering leaders to deliver key product metrics and user behavior insights

As an Analytics Data Engineering Manager focused on Product, you will build and lead the analytics engineering team responsible for creating the data foundations that enable data-driven decision making across Anthropic’s Product organization.  You will oversee the development of scalable data solutions for Product pillars – including Consumer, Claude Code, Enterprise & Verticals, Growth, Platform Product – managing a team of analytics engineers and working closely with stakeholders across Data Science, Product, and Engineering to ensure teams have access to reliable, accurate metrics that can scale with our company’s growth.

In this role, you will balance hands-on technical leadership with people management, setting the strategic vision for product data foundations while developing and mentoring team members.  You will partner closely with Product Data Scientists, Product Managers, and Product Engineers to understand how users interact with Claude, how to measure product quality and growth, and how to transform raw event logs into insightful data marts that power product decisions.

Build and scale the Product Analytics Engineering team, including hiring and mentoring a team of high-performing analytics engineers embedded with Product pillars

Define and execute the strategic roadmap for product data foundations and analytics capabilities

Oversee the design and implementation of scalable data pipelines, data models, and analytics solutions that transform raw product event logs into canonical datasets and insightful data marts

Partner with Data Science, Product, and Engineering leadership to understand data needs and translate them into technical requirements