Senior Data Engineer

white circle • United Kingdom

Relocation

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AI Summary

Design, build, and maintain production data pipelines for ingestion, transformation, and orchestration. Model and structure data in a warehouse to support engineering, product, and research teams. Own end-to-end data infrastructure with a focus on reliability, performance, and cost.

Key Highlights

Production data pipelines and warehouse ownership from day one

Full-stack data engineering with SQL, Python, and modern data stack

Real-time data integration from diverse sources including web scraping

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Key Responsibilities

Design, build, and maintain production data pipelines for ingestion, transformation, and orchestration

Model and structure data in the warehouse to be clean, documented, and usable across teams

Own data infrastructure including schema design, migrations, performance, and cost

Provide data support to GTM engineers with curated company and account data

Integrate and route diverse data sources into the warehouse from internal events and third-party feeds

Occasionally build data-extraction jobs including web scraping when needed

Improve data quality, observability, and documentation

Diagnose and fix pipeline issues before they become problems

Jump into data and infra tasks to make systems more robust

Technical Skills Required

Python SQL Data Modeling

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Benefits & Perks

Paid time off in line with local regulations

Best medical insurance in France

Hardware, tools, and services provided

Subscriptions for AI agents and IDEs

Team off-sites twice a year

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Nice to Have

Streaming/eventing (e.g., Kafka)

Versioning datasets and lightweight data pipelines

dbt for data modeling

Modern ETL tools (Fivetran, Airbyte, dlt)

AWS services (Athena, Glue, S3)

GTM/CRM data workflows and enrichment tools

Web-scraping experience

Rust for internal data tooling

Job Description

White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale.

We’ve raised $11M from top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others
We process over one hundred million API calls every month
We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model

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