Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Kafka @ 2
Python @ 5
SQL @ 5
Looker @ 3
Spark @ 3
Tableau @ 3
dbt @ 3
ETL @ 5
Airflow @ 3
Kinesis @ 2
Communication @ 3
Data Engineering @ 3
ELT @ 5
CCPA @ 2
GDPR @ 2
Fraud @ 3
Reporting @ 3
Snowflake @ 3
Compliance @ 2
AI @ 3
Data Pipelines @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The Safeguards team works to monitor models, prevent misuse, and ensure user well-being. This Data Engineer role will build the data foundations that keep Anthropic's AI systems safe by designing and implementing data pipelines, warehousing, and analytical tooling to support safety and trust efforts at scale.
Responsibilities
- Design, build, and maintain scalable data pipelines that support safety monitoring, abuse detection, and enforcement workflows
- Develop and optimize data models and warehousing solutions to enable efficient analysis of large-scale usage and safety data
- Build and maintain dashboards and reporting infrastructure that give Safeguards teams visibility into model behavior, misuse patterns, and enforcement outcomes
- Collaborate with engineers to integrate data from multiple sources — including model outputs, user reports, and automated classifiers — into a unified analytical layer
- Implement data quality frameworks, monitoring, and alerting to ensure the reliability of safety-critical data
- Partner with research teams to surface data insights that inform model improvements and safety interventions
- Develop self-service data tooling that enables stakeholders to explore safety data and generate reports independently
- Contribute to data governance practices, including access controls, retention policies, and privacy-compliant data handling
Requirements
- 3+ years of experience in data engineering, analytics engineering, or a related role
- Proficient in SQL and Python, with experience building and maintaining ETL/ELT pipelines
- Hands-on experience with modern data stack tools such as dbt, Airflow, Spark, or similar orchestration and transformation frameworks
- Experience with cloud data platforms (BigQuery, Redshift, Snowflake, or similar)
- Comfortable building dashboards and data visualizations using tools like Looker, Tableau, or Metabase
- Experience translating complex data concepts for both technical and non-technical audiences
- Experience or interest in trust & safety, integrity, fraud, or abuse detection data systems is valuable
- Familiarity with large-scale event streaming systems (Kafka, Pub/Sub, Kinesis) and with ML model monitoring or evaluation is a plus
- Familiarity with data privacy and compliance frameworks (GDPR, CCPA, or similar) is a plus
Compensation
- Annual Salary: £170,000 - £220,000 GBP
Logistics
- Location: London, UK
- Location-based hybrid policy: staff are expected to be in one of Anthropic's offices at least 25% of the time (some roles may require more office time)
- Education requirements: at least a Bachelor's degree in a related field or equivalent experience
- Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to help with the process, though sponsorship is not guaranteed for every role and candidate
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours and a collaborative office environment
About Anthropic
Anthropic is a public benefit corporation headquartered in San Francisco, focused on building safe and steerable AI systems. The organization emphasizes collaboration, communication, and large-scale research efforts in AI safety and related directions.