Analytics Engineering Manager
Anthropic
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
As an Analytics Engineering Manager, you will lead and build the Analytics Engineering team responsible for creating the foundation that enables data-driven decision making across Anthropic. You will oversee the development of scalable data solutions, manage a team of analytics engineers, and work closely with stakeholders across Data Science, Engineering, Product, GTM, and other areas to ensure teams have access to reliable, accurate metrics that can scale with our company's growth. In this role, you'll balance technical leadership with people management, setting the strategic vision for our data infrastructure while developing and mentoring team members.
Responsibilities
- Lead and scale the Analytics Engineering team, including hiring and mentoring a team of high performing analytics engineers
- Define and execute the strategic roadmap for data infrastructure and analytics capabilities across the organization
- Oversee the design and implementation of scalable data pipelines, data models, and analytics solutions
- Partner with Data Science, Engineering, Product, GTM, and other 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 the company
- Collaborate with cross-functional leaders to influence product and GTM roadmaps from a data systems perspective
- Foster a culture of technical excellence, continuous learning, and data-driven decision making
- Manage resource allocation, project prioritization, and team capacity planning
- Serve as a technical thought leader for data modeling, ETL processes, and analytics infrastructure
You may be a good fit if you have
- 5+ years of experience managing analytics engineering or data engineering teams, preferably in a scaling startup environment
- 10+ 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
- Proven track record of building and leading high-performing teams
- Strong technical foundation with expertise in SQL, Python, dbt, and modern data stack tools
- Experience partnering with Product, Engineering, and GTM leaders to deliver key company-wide metrics
- Demonstrated ability to balance strategic thinking with hands-on technical leadership
- Excellence in stakeholder management and cross-functional collaboration
- Strong communication skills with the ability to translate complex technical concepts for diverse audiences
- Experience scaling analytics functions from early stage to maturity
- Track record of establishing data governance, quality standards, and best practices
- A passion for Anthropic's mission of building helpful, honest, and harmless AI
Strong candidates may also have
- Experience building analytics engineering functions from scratch at high-growth startups
- Background in AI/ML companies or similar technical domains
- Expertise with cloud data warehouses (BigQuery, Snowflake, etc.) and orchestration tools
- Track record of implementing self-service analytics platforms
- Experience with data governance and compliance in regulated industries
- Prior experience in a player-coach role, balancing hands-on technical work with management
- Contributions to open-source data tools or communities
The expected salary range for this position is:
Logistics
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
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.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.