Data Engineer

Anthropic Limited; Washington; Híbrido; USD 320.000 - 405.000; Jornada completa

Descripción de la vacante

Anthropic Limited is seeking a Data Engineer for GTM data foundations. You will build a data product layer that combines internal and external sources, enabling sellers, operators, and analysts to gain a current, trusted view of the market.

This role goes beyond pipelines, defining attributes, sources of truth, and how the business leverages data. You will work at the intersection of sales, data, and systems, partnering with Sales Strategy, Finance, Data Science, and central data engineering.

Formación

• Experience building and operating production data pipelines.
• Strong SQL and Python, with modern transformation and orchestration tooling on a cloud data warehouse.
• Experience making messy multi-source data usable, including record matching and deduplication.
• Familiarity with go-to-market data and CRM systems.
• Judgment balancing data sources and business requirements for data quality.
• Clear written and verbal communication with technical and non-technical partners.
• Regular hands-on use of AI tools in engineering work.

Responsabilidades

• Bring disparate internal and external sources together: orchestrate, model, and normalize first-party product and revenue data with third-party data.
• Build and maintain identity and entity resolution for a single trusted record per company and clear relationships.
• Help define the canonical data layer with sourcing, provenance, and freshness.
• Turn data into intelligence: scores, signals, and AI-generated attributes for GTM prioritization.
• Deliver intelligence to surfaces like the CRM and enforce production discipline for data movement.
• Operate the data platform as a living system with observability, data quality, cost, security, and access controls.
• Collaborate with GTM process owners to define, commit, and communicate tradeoffs.
• Make the platform easy for other teams to build on, avoiding silos.

Conocimientos

SQL & Python

Data modeling

Data warehousing

Record matching

Cloud data warehouse

Stakeholder collaboration

Educación

Bachelor's degree

Herramientas

Airflow

dbt

Salesforce

Descripción del empleo

About the company

the company’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

the company's go-to-market teams are scaling quickly, and the decisions they make, from who to sell to and how to cover them to where to invest next, are only as good as the intelligence and infrastructure underneath them. As a Data Engineer on the GTM Systems data foundations team, you'll help build that layer: the data products that give sellers, operators, and analysts a rich, current, and trusted picture of the market, and the engineering rigor that lets our GTM systems run reliably as the business grows.

This is an engineering role that goes beyond pipelines. You'll treat GTM data as a product and a platform: built once, kept current, and available wherever people work. Alongside the build, you'll help shape what the data means: how attributes are defined, which sources are trusted, and how the business puts them to use. The role sits at the intersection of the sales organization, the data organization, and the systems that data flows through. You'll partner closely with Sales Strategy and Operations, Finance, Data Science, and the central data engineering team.

Key responsibilities

• Bring disparate internal and external sources together: orchestrate, model, and normalize first-party product and revenue data alongside third-party data into one usable understanding of the company landscape
• Build and maintain identity and entity resolution, so every source attaches to one trusted record for each company and the relationships between companies are clear
• Help build the canonical layer where key attributes are defined once and mean the same thing everywhere, with clear sourcing logic, provenance, and freshness
• Turn data into intelligence: scores, signals, and AI-generated attributes that help GTM teams prioritize and act, held to the same quality bar as any other source
• Deliver that intelligence to the surfaces where teams work, including the CRM, and bring production discipline to how data moves through those systems
• Operate what you build as a living system, with observability, data quality, cost, security, and access controls designed in, so problems surface before the field sees them
• Partner with the owners of GTM processes such as planning, segmentation, and routing to settle definitions, make clear commitments, and communicate tradeoffs
• Make the platform easy for other teams to build on, so work is contributed once and not rebuilt in silos

Minimum qualifications

• Experience as a data engineer or analytics engineer building and operating production pipelines and data models
• Strong SQL and Python, and experience with modern transformation and orchestration tooling on a cloud data warehouse
• Experience making messy data from many sources usable, including record matching, deduplication, and reconciling conflicting values
• Familiarity with go-to-market data and the CRM systems it flows through
• Judgment beyond the pipeline: weighing data sources, shaping definitions with business partners, and making calls on data quality
• Clear written and verbal communication with technical and non-technical partners
• Regular hands-on use of AI tools in your engineering work

Preferred qualifications

• 5+ years of experience in data engineering, analytics engineering, or GTM data roles
• Experience building a shared data product or platform that several teams depend on and contribute to
• Experience with company data such as firmographics, corporate hierarchies, or master data management
• Experience using LLMs inside data pipelines and evaluating their output
• Hands-on Salesforce experience, including working at large data volumes
• Experience supporting GTM planning processes such as territory design, segmentation, or scoring

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

LogisticsMinimum 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.

How we're different

We believe that the highest-impact AI research will be big science. At the company 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