Top Data Engineer Jobs in Paris

As a Backend Engineer (Data Engineering), design and build scalable data pipelines and infrastructure for processing security data, ensuring reliability and performance.

As an AI & Data Software Engineer, you'll develop web applications, integrate AI features, and collaborate with teams to optimize workflows. You will write code, build APIs, and advocate for AI advancements while maintaining high development standards.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

As a Senior Data Engineer, you will design and optimize data pipelines and warehouses, ensuring data integrity and facilitating access for informed decision-making within Dashlane.

Build and optimize data pipelines and models, monitor cloud data warehouses, and maintain documentation while collaborating with teams.

As a Senior Software Engineer, you'll design and scale data ingestion services, improve system reliability, and mentor teammates. Experience in high-traffic systems and a strong knowledge of Go, Kubernetes, and Google Cloud are essential.

Lead the design and implementation of strategic data architecture, develop and maintain data pipelines, ensure data governance and quality, and mentor team members.

Join the Data Lab team at Coface to design, develop, and deploy Machine Learning solutions, contributing to innovative projects and knowledge sharing.

Design and maintain ETL pipelines, ensure metadata quality at scale, develop solutions for data reconciliation, and collaborate with teams to enhance catalog performance.

As a Senior MLOps, you'll build and maintain data pipelines, design data storage solutions, and deploy model-serving systems, collaborating with ML Engineers for performance and quality.

The Senior Data Engineer will design and optimize data pipelines using Microsoft Azure technologies, collaborating with teams to ensure solutions are scalable and business-aligned.

This role involves building client relationships, demonstrating the value of Databricks' platform, and providing technical expertise to support AI and data strategies.

As a Senior Data Engineer, you will design and scale data systems, build ETL pipelines, ensure data quality, and collaborate with product, growth, and finance teams to support decision-making and analytics.

As a Staff Engineer on the Data platform team, you will develop tools for data quality and lineage while collaborating with cross-functional teams. Responsibilities include setting technical goals, mentoring engineers, and establishing best practices.

The Senior Data AI Engineer will design, build, and scale AI features, prototype ML models, and maintain AI pipelines in a collaborative environment.

As a Staff Engineer and Team Lead, you will architect scalable backend systems, mentor engineers, and ensure high-quality code for Alpaca's market data suite.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

The Senior Software Engineer will develop and scale backend services, manage data pipelines, and ensure system reliability across multi-cloud environments.

The Senior Software Engineer will design and build scalable backend services, improve data pipelines, and ensure system reliability and performance.

The Senior Software Engineer will design and build scalable backend services, integrate data pipelines, and ensure reliability and performance in a multi-cloud environment.

The Senior Software Engineer will design and build backend services, work on data pipelines, and ensure system reliability and performance in a multi-cloud environment.

The Senior Data Engineer will design scalable systems, automate ML operations, optimize performance, and enhance infrastructure for data processing and monitoring.

Design and maintain data pipelines, collaborate with stakeholders, ensure data quality, deploy infrastructure as code, and optimize reporting solutions.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.