In Data Operations on the Strategic Data Partnerships team at Anthropic, you will support a cross-functional team in implementing partnership strategies to improve Anthropic’s products. You’ll ensure data meets our standards and reaches the right teams, build systems to track compliance and data usage across the portfolio, and coordinate across Research, Product, Legal, and external partners to remove barriers and accelerate impact.
This role requires operational excellence combined with technical hands-on execution, and is a great fit for someone who wants to apply those skills in a high-impact, fast-growth context.
Responsibilities:
Data Opportunity Assessment and Processing
- Analyze and review incoming or prospective data to verify it is useful and strategic for Anthropic
- Own and maintain Python-based ETL pipelines that process large partner datasets, applying filtering criteria and deduplicating against existing data
- Write and optimize SQL queries against large relational databases to support filtering and analysis workflows
- Refine processing logic as requirements evolve across new data types and formats
Data Delivery Infrastructure, Tooling, and Support
- Own end-to-end data delivery workflows, ensuring data moves seamlessly from partners to internal teams to accelerate time-to-impact
- Manage AWS and GCP resources for receiving and organizing partner data deliveries
- Troubleshoot delivery issues and coordinate with partners on formatting and transfer protocols and resolve technical escalations from partners and internal teams
- Build and maintain internal systems, scripts, and automation that support the team’s workflows
- Support occasional research evaluation tasks as needed
Data Operations and Governance
- Develop and maintain Anthropic's preferred standards for receiving, consuming and cataloging data, ensuring alignment with Product and Engineering's evolving needs
- Contribute to systems for monitoring data usage and compliance with partner agreements
- Partner with teammates and cross-functional stakeholders to build out governance practices as the team scales
You May Be a Good Fit If You
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience
- 5-7+ years of experience with data pipelines or data engineering workflows
- Background in solutions engineering, partner engineering or related role at a large tech company
- 5+ years of experience in technical troubleshooting or writing code in one or more programming languages
- Proficiency in Python and SQL, including writing, debugging, and optimizing scripts and queries against large datasets
- Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), including managing storage, configuring access, and working from the CLI
- Excellent problem-solving skills with a track record of debugging technical issues, whether at the code level or within a broader system
- Some experience interacting with external third parties delivering data
Strong Candidates Will Have
- Experience working alongside technical teams (research, engineering, or product) to solve ambiguous problems
- Ability to translate technical concepts into clear, actionable guidance for non-technical stakeholders or external partners
- Experience owning or maintaining a production service or system with uptime expectations
- Familiarity with data governance, compliance, or rights management
- Ability to manage multiple, time-sensitive projects simultaneously and the drive to take a project from an initial idea to full completion
- Experience leveraging AI to automate workflows
Candidates Need Not Have
- Deep expertise in AI or machine learning
- A pure software engineering background
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