Data Engineer - GTM Systems Data Foundations

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems that benefit society. As our go-to-market teams scale rapidly, the operational decisions made across sales, territory planning, and account coverage rely directly on the infrastructure and data products built beneath them.

As a Data Engineer on the GTM Systems Data Foundations team, you will treat go-to-market data as both a product and a platform. Sitting at the intersection of Sales Strategy, Finance, Data Science, and Central Data Engineering, you will build data pipelines and canonical data models that unify first-party product usage and revenue data with third-party firmographic sources. You will architect master data management (MDM) layers, identity and entity resolution systems, and AI-driven sales intelligence signals, delivering trusted, current market insights directly to sales surfaces like Salesforce.

Key Responsibilities

• Multi-Source Data Orchestration: Ingest, normalize, and model disparate first-party usage/revenue data and third-party firmographic sources into a unified cloud data warehouse landscape.
• Identity & Entity Resolution: Build and maintain master data management systems that perform deduplication, record matching, corporate hierarchy mapping, and cross-source record linking.
• Canonical Layer Architecture: Establish single-source-of-truth business attributes with clear provenance, auditability, freshness guarantees, and strict security controls.
• AI-Generated Sales Intelligence: Integrate Large Language Models (LLMs) into data pipelines to generate predictive scores, buyer signals, and account attributes held to high production quality standards.
• CRM & Production Integration: Streamline data movement between central warehouses and field surfaces (e.g., Salesforce), maintaining production discipline, observability, and cost controls.
• Process & Stakeholder Alignment: Partner with Sales Ops, Finance, and Data Science leads to settle attribute definitions and support GTM planning (territory design, segmentation, lead routing).
• Platform Development: Build extensible, self-serve data models and utilities that prevent internal silos and enable other engineering teams to build on top of the foundation.

Requirements

Core Technical & Engineering Skills

• Proven background as a Data Engineer or Analytics Engineer building, monitoring, and operating production data pipelines and data models at scale.
• High proficiency in Python and SQL, along with hands-on experience using modern transformation and orchestration tools (e.g., dbt, Airflow, Dagster) on cloud data warehouses (Snowflake, BigQuery, Databricks).
• Demonstrated experience resolving messy, unstructured datasets—including record matching, entity deduplication, and reconciling conflicting multi-source attributes.
• Practical familiarity with Go-to-Market data architectures and Customer Relationship Management (CRM) platforms.
• Hands-On AI Usage: Regular, active integration of AI software development tools into your daily engineering workflow.

Education & Work Logistics

• Bachelor’s degree (or equivalent professional experience/training) in Computer Science, Data Engineering, Information Systems, or a related field.
• Ability to meet Anthropic's hybrid work policy (at least 25% time onsite in office).

Preferred Qualifications

• 5+ years of professional experience in data engineering, analytics engineering, or dedicated GTM data infrastructure roles.
• Prior experience building a shared, central data product or platform relied upon by multiple cross-functional teams.
• Domain expertise handling firmographics, corporate hierarchies, and Master Data Management (MDM) frameworks.
• Experience embedding LLMs directly inside data pipelines and constructing output evaluation benchmarks.
• Hands-on Salesforce data engineering experience, specifically operating at high data volumes.
• Practical experience supporting GTM operational processes such as territory planning, lead scoring, or account segmentation.

Total Rewards & Benefits

• Compensation & Equity: Base salary of $320,000 – $405,000 USD + competitive equity package with optional equity donation matching.
• Healthcare & Family Support: Comprehensive health, vision, and dental coverage; generous paid parental leave.
• Time Off & Flexibility: Flexible working hours and generous PTO policy.
• Workplace & Perks: Office space in San Francisco, collaborative research environment, and full visa sponsorship support through external immigration counsel.