Top Data Engineer Jobs in France

Lead the architecture, optimization, and reliability of large-scale batch and streaming data infrastructure. Mentor two data engineers, establish engineering standards, oversee delivery, and ensure monitoring, automated data-quality testing, security, and GDPR compliance. The role requires deep expertise in distributed databases, Kafka, Kubernetes, on-premise infrastructure, column-oriented and vector databases, and programming with Python, Golang, Scala, or Java. It also involves collaborating cross-functionally and promoting DataOps, CI/CD, and Generative AI adoption.

Build and own the architecture for Dune’s curated data lifecycle, including dependency-aware orchestration, backfills, schema evolution, retries, recovery, data quality, and alerting. The role combines backend software engineering with large-scale data systems work across Go, Kotlin, Rust, Python, and SQL. Responsibilities include designing ingestion and curation contracts, making architecture decisions, solving ambiguous problems, and leading work that other engineers can execute.

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.

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.

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

Owns the full lifecycle of pricing data products, including data pipeline ownership, architecture, production-quality coding, and ML system infrastructure. Collaborates with data scientists and cross-functional teams to deploy real-time pricing algorithms, scale ML infrastructure, optimize performance, and build enterprise data warehouses, marts, dashboards, and KPI metrics. The role also manages orchestration, cloud infrastructure, DevOps, data governance, GDPR compliance, and stakeholder communication.

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 and build durable, distributed data-streaming infrastructure that decouples process data from Camunda’s live execution engine. Develop customer-facing integrations such as Kafka connectivity, support analytics data consumption at scale, and make architecture decisions around consistency, durability, and storage. Participate in production support and on-call rotations while collaborating with Product, Data Layer, Distributed Systems, QA, SRE, and Support teams. Lead ambiguous, cross-functional engineering initiatives from design through delivery.

Build and maintain Camunda 8 backend data-layer services spanning relational databases and Elasticsearch/OpenSearch. Design scalable storage, query, retention, and streaming systems; improve performance, indexing, and production tooling. Lead engineering initiatives from solution design through delivery, collaborate across teams, provide L3 support, and participate in on-call rotations. Investigate production data issues and contribute to schema evolution, workflow automation, and CI improvements.

Design and operate production data pipelines and standardized data models for a multi-tenant Azure SaaS platform serving container terminals. Build near-real-time and batch ELT pipelines from operational systems, develop Go-based connectors, implement data quality monitoring, and support source-to-curated transformations across PostgreSQL layers. Collaborate directly with terminal operations staff while owning architectural decisions and platform scalability.

Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. Translate business needs into scalable data models and reliable data products, improve data quality and observability, resolve production issues, and establish reusable engineering tools and standards. Collaborate with product and business stakeholders, contribute to architecture decisions, mentor engineers, and participate in on-call support.

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

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

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

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

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.

Lead data engineering initiatives across large-scale e-commerce datasets. Own data models, transformation architecture, analytics projects, client data products, internal dashboards, documentation, and technical roadmap delivery. Collaborate with technical and business stakeholders, mentor teammates, and translate business needs into scalable data solutions using SQL, BigQuery, Google Cloud, ETL/ELT tools, and visualization platforms.

Design, build, and operate ingestion, curation, versioning, and delivery pipelines that convert terabytes of raw, unstructured multimodal field and public data into training-ready datasets. Align multimodal streams, define labeling requirements, enable reproducible dataset lineage, optimize storage and I/O for model training, and provide tooling for dataset construction and loading.

Design, build, and operate batch and streaming data pipelines; move production data into data lakes; ensure dataset quality, freshness, and observability; optimize queries and processing for correctness, latency, and cost; prototype and integrate production experiments; build reusable derived datasets.

The Senior Python Developer will build and enhance data platforms for quantitative trading, ensuring code quality and performance while collaborating with teams.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.

The role involves automating OpenSearch operations by developing features in Python, collaborating with an international team, and providing expertise on data platforms.

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

Lead SRE for Edenred's Data & AI platform: define and operate SRE standards, observability, FinOps, incident and service management; co-own CI/CD and architecture; act as player-coach to improve reliability and run critical systems.