12 days ago
Base Salary
$320k - $405k/yr
Responsibilities
- Integrate, orchestrate, model, and normalize first-party product and revenue data with third-party data.
- Build and maintain identity resolution, entity resolution, record matching, deduplication, and trusted company records.
- Create canonical data layers with consistent attribute definitions, sourcing logic, provenance, and freshness.
- Develop scores, signals, and AI-generated attributes to support GTM prioritization and decision-making.
- Deliver data products to CRM and other team workflows while operating reliable production data systems.
- Design observability, data quality, cost, security, and access controls into the platform.
- Partner with Sales Strategy and Operations, Finance, Data Science, and other GTM process owners on definitions, planning, segmentation, routing, and tradeoffs.
- Build a shared platform that other teams can contribute to and reuse.
Requirements
- Experience as a data engineer or analytics engineer building and operating production pipelines and data models.
- Strong SQL and Python skills and experience with modern transformation and orchestration tooling on a cloud data warehouse.
- Experience making multi-source data usable through record matching, deduplication, and reconciliation of conflicting values.
- Familiarity with GTM data and CRM systems.
- Ability to evaluate data sources, define data standards with business partners, and make data-quality decisions.
- Clear written and verbal communication with technical and non-technical partners.
- Regular hands-on use of AI tools in engineering work.
- Preferred: 5+ years in data engineering, analytics engineering, or GTM data roles.
- Preferred: experience building shared data products or platforms, working with firmographics or corporate hierarchies, using LLMs in data pipelines, evaluating LLM output, hands-on Salesforce experience at large data volumes, and supporting territory design, segmentation, or scoring.
Benefits
- Annual base salary range of $320,000—$405,000 USD.
- Visa sponsorship is offered with reasonable efforts made to obtain a visa if an offer is extended, though sponsorship is not successful for every role or candidate.
- Hybrid policy: staff are generally expected to work from one of the company’s offices at least 25% of the time, with some roles requiring more office time.
- Competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.
- Minimum education is a bachelor’s degree or equivalent combination of education, training, and/or experience; relevant field of study may be demonstrated through coursework, training, or professional experience.
About Anthropic
Anthropic builds large language models and the Claude AI assistant for developers and enterprises, offered via API access and enterprise plans. Founded in 2021 and headquartered in San Francisco, it distributes Claude through its own platform and via partners such as Amazon Bedrock and Google Cloud’s Vertex AI. Its work emphasizes model reliability, interpretability, and practical tooling for tasks like coding assistance, analysis, and customer support automation.