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Home / Data Engineer

Data Engineer

  • Full Time
  • Anywhere

About Mistral

Source: Wikipedia

Mistral

About Mistral 
 
At Mistral AI, we believe in the power of AI to simplify tasks, save time and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.
 
We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.
 
We are a dynamic, collaborative team passionate about AI and its potential to transform society.
Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.
 
Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.
 
Role summary

We are seeking passionate and talented Data Engineers to join our team. Candidates with an Analytics Engineering background are also encouraged to apply.
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.

Hiring process
• Intro call with Recruiter – 30 min
• Hiring Manager Interview – 30 min
• Technical interview – Live Coding (Python/SQL) – 45 min
• Technical interview – System Design – 45 min
• Value talk interview – 30 mins
• References
 
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To apply for this job please visit jobs.lever.co.

About this role & career path

Working in Paris

Paris is the capital and largest city of France, with an estimated city population of 2.04 million in an area of 105.4 km2 (40.7 sq mi), and a metropolitan population of 13.2 million as of January 2026. Located on the river Seine in the centre of the Île-de-France region, it is the largest metropolitan area and fourth-most populous city in the European Union (EU). Nicknamed the "City of Light", partly because of its role in the Age of Enlightenment, Paris has been one of the world's major centres of finance, diplomacy, commerce, culture, fashion, and gastronomy since the 17th century.

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