Top Data Engineer Jobs in France

Lead design and delivery of AI-powered visualization and investigation features using LLMs. Build reliable, explainable systems combining deterministic product capabilities with generative models, drive prompt/context engineering, evaluation frameworks, and cross-team product-focused technical leadership and mentorship.

Lead technical direction and hands-on implementation of semantic infrastructure for telemetry interoperability. Build scalable systems bridging OpenTelemetry, cloud and customer data models; define standards, mentor engineers, run on-call rotations, and drive cross-team platform initiatives for schema evolution and AI-enabled observability features.

Design, develop, and maintain scalable data pipelines and ETL processes. Ensure data quality, troubleshoot data issues, integrate data solutions with cross-functional teams, mentor junior engineers, and drive continuous improvement of data engineering tools and processes.

Lead development and production deployment of index calculations and analytics on Dataiku. Design scalable data pipelines, write robust Python code, perform peer reviews, document solutions, and monitor/improve production performance in collaboration with business stakeholders.

The Senior Software Engineer will scale the Supplier Data Manager for enterprise customers, enhance AI-driven data pipelines, and improve collaboration features while ensuring operational excellence and customer-driven product development.

Design, build, and maintain scalable data pipelines and storage for fraud detection. Support fraud analytics, feature engineering, model integration and serving, pipeline monitoring, and documentation. Collaborate with data, product, and engineering teams to enable detection, reporting, and operationalisation of fraud models.

Design, build, and operate enterprise reporting and analytics platforms. Create scalable ELT/ETL pipelines, master data foundations, and lakehouse/warehouse semantic models. Deliver Power BI datasets and dashboards, implement data quality, governance, DevOps practices, and cost-management data solutions. Partner with finance and stakeholders and provide technical leadership across architecture, deployment, and run-state support.

The Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

The IT/OT Data Engineer is responsible for data collection, architecture development, building data pipelines, and collaborating with data scientists to improve data reliability and efficiency.

Build, optimise and maintain the retail data platform. Collaborate with product and business teams to deliver data-driven products. Design scalable data and AI architectures and models, develop and manage ETL/ELT pipelines (Spark/Databricks), ensure high platform availability, and enable transition and adoption across teams.

Build and operate scalable ETL/ELT pipelines to ingest, transform, and model data across Palantir Foundry and Databricks. Ensure data quality, lineage, observability, and access controls. Collaborate with analysts and product teams to translate requirements into reliable, documented datasets and establish standards, monitoring, and automation for production data flows.

As a Data Analyst, you will analyze data to drive insights, create reports and dashboards, and collaborate with teams to optimize product performance.

As a Data Engineer, build and optimize high-performance data infrastructures for deep learning by managing large volumes of raw video data, ensuring efficient processing pipelines and data quality.

The Clinical Data Engineer will manage data pipelines for clinical studies, ensuring data integration and analysis for hardware validation and product accuracy. The role involves close collaboration across teams and requires expertise in data engineering, statistical modeling, and biometrics.

As the Data Engineer, you will design and maintain data pipelines, scale data infrastructure, ensure data quality, and collaborate with analysts to enhance decision-making capabilities.

Build and maintain GTM systems and data pipelines: design data models, develop internal FastAPI/React apps, lead an OpenAI Agent-based GTM AI layer, drive architecture and CI improvements, perform code reviews, and collaborate with Sales, RevOps, Data, and R&D to increase adoption and reliability.

Design, build, and operate petabyte-scale batch, streaming, and reporting pipelines. Optimize storage and compute (lakehouse), own ClickHouse/Cube reporting contracts, lead on-call and incident response, build alerts/SLOs/runbooks, and influence upstream schemas and SLAs.

As a Data Engineer, you will develop data pipelines, collaborate with data scientists, and deploy cloud infrastructures, while participating in community events.

Design, build, and maintain large-scale data pipelines and tooling for petabyte-scale logs, events, and model traces. Ingest, clean, transform, version, and monitor datasets; ship analytics and dashboards; support production, testing, and research workloads; troubleshoot pipeline issues and improve reliability.

The Data Engineer will develop data pipelines, collaborate with data scientists, deploy cloud infrastructure, and contribute to community knowledge.

As a Data Engineer, you will develop data pipelines, support data scientists, deploy cloud infrastructure, and collaborate within the data community.

The Data Engineer will develop data platforms in the cloud, create data pipelines, collaborate with data scientists, and deploy infrastructures using infra-as-code.

Develop data pipelines, support data scientists, deploy cloud infrastructures, and engage in community events. Requires strong data engineering skills and collaboration.

As a Data Engineer, you will develop data pipelines, support data scientists, deploy cloud infrastructure as code, and participate in the data community.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.