Analytics Data Engineering Manager, Product

Responsibilities:

• 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
• Establish and maintain high data integrity standards, SLAs, alerting, and best practices for the team
• Drive the development of foundational data products, dashboards, and tools to enable self-serve analytics; partner with the Data Science team to build innovative data tools using Claude to scale data-driven decisions across Product teams
• Foster a culture of technical excellence, continuous learning, and data-driven decision making
• Serve as a technical thought leader for data modeling, ETL processes, and product analytics infrastructure

You might be a good fit if you have:

• 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
• Demonstrated ability to balance strategic thinking with hands-on technical leadership
• Strong communication skills with the ability to translate complex technical concepts for diverse audiences
• Experience scaling analytics functions from early stage to maturity in rapidly changing environments
• Track record of establishing data governance, quality standards, and best practices
• A bias for action and urgency, not letting perfect be the enemy of the effective
• A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end
• A passion for Anthropic’s mission of building helpful, honest, and harmless AI

The annual compensation range for this role is listed below. 

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:

$370,000 - $450,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.