Data Engineering Manager, GTM & Marketing

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.

As a Data Engineering Manager focused on GTM & Marketing, you will build and lead the data engineering team responsible for turning complex commercial data into the trusted foundations that power decision-making across Anthropic's GTM and Marketing organizations. You will partner closely with stakeholders across Data Science, Revenue Operations, Marketing, and Finance to connect the needs of our customers to the dynamics of our pipelines — from new logo acquisition through activation, expansion, and retention — for a rapidly scaling, consumption-based AI platform.

In this role, you will balance hands-on technical leadership with people management, setting the strategic vision for GTM and Marketing data foundations while developing and mentoring your team. You will oversee the transformation of CRM, marketing automation, billing, usage, and third-party data into canonical datasets and insightful data marts — owning the metric definitions that Sales, Marketing, Finance, and leadership rely on to run the business.

• →Build and scale the GTM & Marketing Data Engineering team, including hiring and mentoring data engineers
• →Define and execute the strategic roadmap for GTM and Marketing data foundations and analytics capabilities
• →Oversee the design and implementation of scalable data pipelines, data models, and analytics solutions that transform CRM (Salesforce), marketing automation, billing, usage, and third-party data sources into canonical datasets and data marts
• →Partner with Data Science, RevOps, Marketing, Finance, and 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 Data Science to build innovative data tools using Claude to scale data-driven decisions across GTM and Marketing 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 GTM/Marketing analytics infrastructure

• Experience managing data engineering teams in a high-growth environment
• Deep expertise in data modeling, ETL pipelines, and data warehouse architecture
• Strong proficiency in SQL, Python, dbt, and modern data stack tools
• Experience modeling GTM and Marketing data domains — including Salesforce/CRM, marketing automation platforms (e.g., Marketo, HubSpot), and billing/subscription/usage data
• Demonstrated experience building and leading high-performing data engineering teams
• Track record of partnering with cross-functional stakeholders (Sales, Marketing, RevOps, Finance) to deliver pipeline, revenue, attribution, and funnel metrics
• Ability to balance strategic thinking with hands-on technical leadership
• Strong communication skills with the ability to translate complex technical concepts for non-technical audiences, including executive stakeholders

• 8+ years of total experience in data engineering or similar data-focused roles, with 5+ years in a people management capacity
• Prior experience in a scaling startup or B2B SaaS environment
• Experience with multi-segment, multi-product B2B sales or commercial analytics, especially with consumption-based revenue models and product-led growth (PLG) motions
• Experience with attribution modeling and account/lead/opportunity hierarchies
• Track record of establishing data governance, quality standards, metric definitions, and best practices at scale
• Experience scaling analytics functions from early stage to maturity in rapidly changing environments
• Comfort operating in ambiguous, fast-moving environments where you must create structure and drive forward progress
• A passion for Anthropic's mission of building safe and beneficial AI

Deadline to apply: None. Applications will be accepted on a rolling basis.

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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

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.

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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.