Data Engineer

European Tech Recruit

Paris

Hybride

EUR 60 000 - 80 000

Plein temps

14 jours+

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Avantages offerts par ce poste

Competitive salary + equity

20 days of paid vacation

Hybrid work from Paris

Top-tier medical insurance

All required hardware and tools

Paid subscriptions for AI tools

Twice-yearly team off-sites

Résumé du poste

A dynamic AI safety startup in Paris is seeking a Data Engineer to architect data pipelines and optimize data performance. You will build a scalable data environment, develop internal APIs, and ensure robust data governance. Ideal candidates have strong skills in SQL and Python, experience with modern data stacks, and can communicate effectively in English. This role offers a competitive salary, equity, and hybrid working arrangements, along with top-tier medical insurance and additional benefits.

Qualifications

Experience in building or scaling modern data stacks in a fast-moving environment.
Strong SQL and Python skills with large datasets.
Fluent communication in English, able to collaborate with engineers.

Responsabilités

Build and maintain a clean, scalable data environment.
Develop internal data APIs, SDKs, and tooling for teams.
Monitor and optimize data performance to ensure fast workflows.
Define and enforce permissions, access controls, and security policies.

Connaissances

SQL

Python

Data stack development

Clear communication

Collaboration

English fluency

Outils

Snowflake

ClickHouse

Metabase

Tableau

Description du poste

Our client is looking for a Data Engineer to architect and build data pipelines from the ground up, capable of handling petabytes of logs, events, and model traces, and to create a clean, dependable environment for production, testing, and research workloads.

This organization is an AI safety startup developing the safety, reliability, and optimization layer for advanced AI systems. A core part of the platform is a natural‑language policy engine: clear rules that define what an AI model should and shouldn’t do. These policies are automatically tested, enforced, and continuously refined at scale.

Its infrastructure processes hundreds of millions of API calls every month, and the team trains and fine‑tunes proprietary LLMs that outperform both open‑source and commercial models on speed and cost.

This is a small, deeply focused team where your work will ship quickly, solve hard problems, and directly shape how AI safety is implemented in real systems.

What You’ll Do

Build and maintain a clean, scalable data environment, enabling teammates to access petabytes of traces, logs, and model outputs in the formats they need—without delays or manual data wrangling.
Develop internal data APIs, SDKs, and tooling that let engineering, product, and research teams discover, query, and use data without managing infrastructure.
Monitor and optimize data performance—from storage layouts to query execution plans—to ensure analytics and research workflows stay fast as data volumes surge.
Own data access and governance, defining and enforcing permissions, access controls, and security policies.

What We’re Looking For

Experience building or scaling a modern data stack (e.g., Snowflake, ClickHouse, event streaming systems) in a startup or similarly fast‑moving environment.
Strong SQL and Python skills, with comfort working on large, noisy datasets.
Clear communication and the ability to collaborate directly with engineers and researchers. Fluent English.
Bonus: experience with Metabase, Tableau, or similar internal dashboarding tools.

Compensation & Benefits