Data Engineer, Product

• Understand, and where possible anticipate, the data needs of partner teams, and translate them into data models, reporting and technical requirements • Define, build and manage key dbt pipelines that turn raw logs into canonical datasets • Set data integrity standards and SLAs so data is delivered on time and accurately • Build reliable dashboards that track core metrics and share insights across the company • Build foundational data products, dashboards and tools that let self-serve analytics scale • Partner with stakeholders to define and materialize metrics and analysis for new and evolving consumer products • Shape Product teams' roadmaps from a data systems perspective • Become an expert in our data models and data architecture You may be a good fit if you have • Significant experience as a Data Engineer or in a similar Data Science & Analytics role, ideally partnering with Product leads to build and report on company-wide metrics • A passion for Anthropic's mission of building helpful, honest and harmless AI • Expertise building multi-step ETL jobs with tools like dbt, plus experience with workflow tools like Airflow and version control through GitHub • Expertise in SQL and Python for turning data into accurate, clean data models • Experience building reporting and dashboards in tools like Hex that serve multiple cross-functional teams • A bias for action, and a sense of when "good enough" beats perfect • An end-to-end mindset: you take ownership of solving a problem fully, even when that means picking up work beyond your usual scope • Comfort with ambiguity, and a habit of creating clarity and forward progress • Experience using AI to scale your own productivity and your team's without lowering the quality of the work

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 a Data Engineer on the Data Science & Analytics team, you'll build the foundation that lets analytics scale across Anthropic. You'll partner with Engineering, Product and other teams to turn raw data into reliable metrics, reporting and insights, and you'll make sure teams have accurate metrics for our consumer products from idea to launch. You'll also lead your own projects that make self-serve insights possible, so teams can make data-driven decisions. Responsibilities • Understand, and where possible anticipate, the data needs of partner teams, and translate them into data models, reporting and technical requirements • Define, build and manage key dbt pipelines that turn raw logs into canonical datasets • Set data integrity standards and SLAs so data is delivered on time and accurately • Build reliable dashboards that track core metrics and share insights across the company • Build foundational data products, dashboards and tools that let self-serve analytics scale • Partner with stakeholders to define and materialize metrics and analysis for new and evolving consumer products • Shape Product teams' roadmaps from a data systems perspective • Become an expert in our data models and data architecture You may be a good fit if you have • Significant experience as a Data Engineer or in a similar Data Science & Analytics role, ideally partnering with Product leads to build and report on company-wide metrics • A passion for Anthropic's mission of building helpful, honest and harmless AI • Expertise building multi-step ETL jobs with tools like dbt, plus experience with workflow tools like Airflow and version control through GitHub • Expertise in SQL and Python for turning data into accurate, clean data models • Experience building reporting and dashboards in tools like Hex that serve multiple cross-functional teams • A bias for action, and a sense of when "good enough" beats perfect • An end-to-end mindset: you take ownership of solving a problem fully, even when that means picking up work beyond your usual scope • Comfort with ambiguity, and a habit of creating clarity and forward progress • Experience using AI to scale your own productivity and your team's without lowering the quality of the work Strong candidates may also have • Experience building a data engineering (or similar) function from the ground up in an early-stage or fast-growing environment 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: $320,000—$405,000 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. 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. 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