Top Data Engineer Jobs in Paris

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

The MES Integration Engineer will manage the deployment and configuration of a Manufacturing Execution System for quantum chip fabrication, focusing on integrating fabrication processes and data management in an R&D environment.

Design, build, and maintain production ELT pipelines for high-volume streaming spatial and telemetry data. Architect Databricks/AWS schemas for ultra-low latency and zero-data-loss. Develop and optimize a central semantic layer using Cube.js for reliable data consumption. Ensure LLM-agent friendly semantic modeling, automation of pipeline unit tests, and package integration blueprints for Professional Services.

Design, build, and operate data infrastructure to process massive event volumes into reliable, low-latency analytics and data products. Own real-time and batch services, platform tooling, observability, cost and performance optimization, on-call incident response, and cross-team stakeholder collaboration to enable analytics, ML, and reporting at scale.

Design, operate, and improve Deezer's data ingestion and platform infrastructure. Maintain and monitor pipelines, support Airflow rollout, schedule GCP jobs on Spark and BigQuery, collaborate with stakeholders, and implement CI/CD, monitoring, and FinOps improvements.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Build end-to-end features for a data orchestration platform across Java/Micronaut backend and Vue 3/TypeScript frontend. Implement data-aware orchestration (assets, lineage, freshness, quality), create integrations/plugins (dbt, Fivetran, Airbyte, warehouses), improve UI (flow editor, topology, dashboards), collaborate on 8-week releases, review PRs, and engage with the open-source community.

Design and build highly scalable, low-latency market data systems and APIs. Implement backend services, influence architecture, maintain test coverage, participate in code reviews, troubleshoot incidents, and occasionally be on-call. Work spans streaming and historical market data endpoints and developer-focused API improvements.

Own and evolve a GCP-native data platform from ingestion to reporting. Lead architecture, reliability, observability, data quality, cost optimization, and AI-assisted engineering practices while mentoring engineers and collaborating with product and customer teams.

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