37 Data Engineer jobs in France available for remote work from home. Apply for positions such as Data Engineer, Software Engineer, Data Infrastructure & Acquisition - Nantes, France, Data Engineer (Marketing-oriented) | Remote for Marketing Agency for Education and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design and build batch and near-real-time data pipelines using PySpark and Databricks within a medallion architecture. You will architect efficient Delta Lake schemas and collaborate with product teams to translate requirements into reliable data enrichment workflows.
The role involves managing data collection and operating cloud infrastructure to support large-scale model training operations. You will collaborate with scientists to optimize data ingestion pipelines and define the dataset roadmap for AI products.
The Senior Data Engineer will own the end-to-end data pipeline architecture, connecting paid media platforms and CRMs into a centralized BigQuery warehouse. They are responsible for building modular transformation pipelines, ensuring data quality, and enabling performant reporting for marketing teams.
You will design and build ELT pipelines to move data from terminal operating systems into a centralized Azure-based platform. Additionally, you will develop transformation layers and maintain a standardized data model to ensure data quality and consistency across global terminals.
The role involves managing data collection and ingestion pipelines to support AI model training operations. You will collaborate with scientists and leadership to optimize infrastructure and define the dataset roadmap for next-generation products.
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Develop and maintain Python backend services and Ruby on Rails codebases while building AI agents for advertising data. Collaborate with cross-functional teams to deliver production-ready features from design to deployment.
The role involves managing data collection and ingestion pipelines to support large-scale model training operations. You will collaborate with scientists and leadership to optimize infrastructure and define the dataset roadmap for next-generation AI products.
You will own the end-to-end Enterprise Data Platform, managing data ingestion, transformation, and quality. You will collaborate with cross-functional teams to build reliable data models, dashboards, and governance frameworks.
The role involves managing data collection and ingestion pipelines to support large-scale model training operations. You will collaborate with scientists and leadership to optimize data infrastructure and define the dataset roadmap for AI products.
You will own the full lifecycle of data products, collaborating with Data Scientists to bring real-time pricing algorithms to production. You will also architect data pipelines, manage infrastructure, and lead cross-team efforts to scale ML development and deployment.
Design, build, and maintain reliable batch and near-real-time data pipelines while enforcing data contracts and governance standards. Collaborate across cross-functional teams to deliver dependable, reusable data products within a regulated fintech environment.
Lead and review the electrical design of hyperscale and mission-critical data centres across all project phases while managing multidisciplinary external consultants. Oversee utility coordination, permitting, and integrated systems testing to ensure project delivery meets design intent and operational requirements.
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows within the Microsoft Fabric ecosystem. Collaborate with cross-functional teams to optimize Spark workloads and ensure high-quality data delivery for analytics and reporting.
You will build and maintain end-to-end features for the Kestra orchestration platform, spanning from the Java backend to the Vue 3 frontend. Additionally, you will collaborate with the product team to develop data-aware orchestration tools and improve integrations with modern data stack technologies.
You will lead the mechanical engineering evaluation of prospective data center sites, including cooling capacity analysis and equipment feasibility reviews. You will also partner with cross-functional teams to define mechanical strategies and ensure technical readiness before construction begins.
You will lead electrical due diligence, utility interconnection analysis, and equipment feasibility reviews to inform strategic infrastructure acquisition decisions. Additionally, you will coordinate with cross-functional teams to define power distribution topologies and ensure construction readiness for AI cloud infrastructure.
Construct and manage robust data pipelines to support evolving business needs while maintaining production code. Collaborate with cross-functional teams including back-end, data science, and product to drive architecture design and feature implementation.
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Build and grow the company's Data Warehouse by developing ETL/ELT pipelines and modeling payment and product data. Create clear dashboards for business teams and implement data validation tests to ensure reliable reporting.
Build and evolve a cloud-native, AI-first data platform that transforms business data into actionable assets for AI agents and humans. Lead the transition from batch-oriented pipelines to real-time streaming systems while improving data observability and governance.
Design and optimize end-to-end data architectures on Microsoft Fabric and Azure, managing the entire data value chain from ingestion to exposure. Provide technical leadership through mentoring, code reviews, and contributing to pre-sales activities and internal practice growth.
Design and develop solutions for data collection, storage, and modeling to ensure high data quality and accessibility for analysts and scientists. Contribute to Big Data cluster standards, data policies, and maintain technological watch on programming languages.
Develop and maintain client use cases using GCP Big Data and Cloud infrastructure while ensuring data security and compliance. Contribute to the internal community through solution benchmarking, Proof of Concepts, and knowledge sharing.
Design and develop solutions for data collection, storage, and modeling while ensuring data quality and accessibility for analysts and scientists. Lead technical teams, manage code quality, and participate in pre-sales and client technical solutions.
Design and develop solutions for data collection, storage, and modeling while ensuring data quality and accessibility for analysts and scientists. Lead technical teams, manage code quality, and participate in pre-sales activities and client technical solutions.
Build and maintain resilient streaming and batch data pipelines to ingest, normalize, and distribute market and trading data. Develop self-serve tooling and data governance frameworks to ensure high-quality, observable, and performant data products across the organization.
You will define the architecture for the data platform and lead the design of scalable, low-latency pipelines for high-volume payment transactions. Additionally, you will mentor senior engineers and partner with cross-functional teams to ensure data reliability and business value.
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The Staff Data Security Engineer will design and implement enterprise data protection capabilities across Microsoft 365, endpoints, and cloud platforms. This role involves collaborating with cross-functional teams to identify, classify, and secure sensitive data while managing DLP policies and DSPM tooling.
![Actian Corporation is hiring for remote AI Augmented Software Engineer [gn] Data Intelligence Platform](/assets/5faaf380-1070-4f64-b725-786eeaa2581e.png){kind=small}
Design and implement full-stack features for the Data Intelligence Platform while leveraging AI tools to accelerate development and improve code quality. Collaborate with product managers and team members to ensure stable, scalable, and maintainable production-grade solutions.
Serve as a trusted technical advisor for strategic accounts, evangelizing Veeam Vault and providing expertise in data resilience and public cloud platforms. Lead architecture reviews, resilience assessments, and technical workshops to drive customer success and secure recovery strategies.
You will own the data and storage self-service layer, building infrastructure and tooling that allow researchers to access and process large multimodal biological datasets independently. You will also create internal services and paved roads to abstract complexity and ensure data security through code.
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