Role summary

We are seeking passionate and skilled Data Engineers to join our team. In this role, you will have the unique opportunity to build, optimize, and maintain our data infrastructure. You will work with large volumes of data, enabling product teams to access secure and reliable data quickly. Your contributions will support our science team in enhancing the quality of our state-of-the-art AI models and help business users make informed decisions.

What you will do

• Design, build, and maintain scalable data pipelines, ETL processes, and analytics infrastructure. Automate data quality checks and validation processes.

• Collaborate with cross-functional teams to understand data needs and deliver high-quality, actionable solutions, eg work closely with machine learning teams to support model training, deployment pipelines, and feature stores.

• Optimize data storage, retrieval, processing, and queries for performance, scalability, and cost-efficiency.

• Define and enforce data governance, metadata management, and data lineage standards.

• Ensure data integrity, security, and compliance with industry standards.

About you

• Master’s degree in Computer Science, Engineering, Statistics, or a related field.

• 3+ years of experience in data engineering, analytics engineering, or a related role.

• Proficiency in Python and SQL.

• Experience with dbt.

• Experience with cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Clickhouse).

• Strong analytical and problem-solving skills, with attention to detail.

• Ability to communicate complex data concepts to both technical and non-technical stakeholders.

Nice to Have

• Experience with machine learning pipelines, MLOps, and feature engineering.

• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).

• Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code (e.g., Terraform).

• Background in building self-service data platforms for analytics and AI use cases.

Location & Remote

The position is based in our Paris HQ offices and we encourage going to the office as much as we can (at least 3 days per week) to create bonds and smooth communication. Our remote policy aims to provide flexibility, improve work-life balance and increase productivity. Each manager can decide the amount of days worked remotely based on autonomy and a specific context (e.g. more flexibility can occur during summer). In any case, employees are expected to maintain regular communication with their teams and be available during core working hours.

What we offer

💰 Competitive salary and equity package

🧑‍⚕️ Health insurance

🚴 Transportation allowance

🥎 Sport allowance

🥕 Meal vouchers

💰 Private pension plan

🍼 Generous parental leave policy