# Data Engineer

**Company**: Anthropic
**Location**: San Francisco, CA
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $320,000-$405,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q116758847

**Apply**: https://job-boards.greenhouse.io/anthropic/jobs/5464234008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_a46bfb35-72a

## Description

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.

As a Data Engineer on the GTM Systems data foundations team, you'll help build 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.

## 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

## Skills

### Required
- SQL
- Python
- data engineering
- analytics engineering
- cloud data warehouse

### Nice to have
- LLMs
- Salesforce
- firmographics
- corporate hierarchies
- master data management

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/anthropic/jobs/5464234008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)