Top Data Engineer Jobs in Paris

Design and build production data pipelines for place and location datasets. Work with large, noisy geospatial data, improve dataset quality and observability, define data-quality metrics, prototype in Python/SQL notebooks, integrate experiments with backend systems, and run offline evaluations and A/B tests.

Design, build and maintain scalable data models, ETL pipelines, and data access layers. Collaborate with product and data science teams to enable analytics and dashboards, participate in agile processes, code reviews, deployment, and monitoring to deliver production-quality data solutions.

The Senior Data Engineer will design and maintain scalable data pipelines, ensure data quality, and develop backend services to support WalletConnect's payments infrastructure and analytics.

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.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

Design, build, and maintain scalable ELT data pipelines with Airflow; develop dbt data models and tests; optimize Athena tables/queries and data workflows; provision infrastructure with Terraform; ensure data quality and reliability; collaborate with Analytics, BI, and Engineering; troubleshoot pipeline and data quality issues.

The Senior Data Engineer will build and maintain data pipelines on GCP for AI models, ensuring data quality and collaborating with teams on data governance.

Design, build, and operate high-volume streaming and batch ingestion pipelines for cardiac device data in a regulated HealthTech environment. Own workflow orchestration, data modeling, warehousing, quality, traceability, observability, deployments, incident response, and on-call operations. Collaborate with Analytics, Product, and Engineering teams while contributing to technical decisions and modernizing the orchestration platform with Temporal.

Responsible for data collection to support model training, finding new audio data sources, and operating the cloud infrastructure for ingestion pipelines.

Build and operate Qonto's data governance framework for banking compliance: define quality rules, implement dbt tests and source controls, monitor and remediate data issues, drive adoption of governance tooling, and automate governance workflows leveraging AI to ensure traceable, audit-ready reporting.

The Data Engineer Intern will assist in building data pipelines, creating relational databases, and supporting data-driven solutions in the space sector.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Founding Data Engineer to design, build and scale AI-first data pipelines and production systems for LLM-powered insurance workflows. Own ingestion, structured extraction, document processing, evaluation/monitoring, APIs and reliability to deliver production-grade AI products used by brokers.

Lead architecture and development of a low-latency trading stack focused on data infrastructure and control workflows. Design high-performance datastores, build a data platform for quantitative research, create control tools to safeguard operations, own systems end-to-end, and mentor engineers while collaborating closely with researchers.

Design, build, and maintain a scalable data platform and ELT pipelines; model data in Snowflake; ingest from PostgreSQL, Elasticsearch and third-party APIs; power BI and product analytics; ensure data quality and governance; collaborate with stakeholders and mentor other engineers.

Design and implement a scalable, real-time data architecture to ingest public data sources, map exposed secrets to organizations, and analyze impact. Lead production deployments, monitoring, and maintenance while mentoring engineers, collaborating with backend/ML/Data teams, and driving roadmap and architectural decisions.

Design, build, and operate scalable data services and pipelines (real-time and batch) powering recommendations, search, and product-facing APIs. Evolve cloud data infrastructure, IaC/CI-CD, observability, and Snowflake data models; integrate AI/LLM features and collaborate across product, backend, and data science teams.

Lead delivery of end-to-end data and analytics solutions: build dimensional models, develop Power BI dashboards, perform exploratory analysis, design Azure-based data pipelines, capture client requirements, run scenario modelling, test and assure solutions, prepare client communications and lead project teams.

Lead data and analytics projects: design dimensional models, build Power BI dashboards, run exploratory analysis, capture client requirements, develop end-to-end data pipelines on Azure, test and assure solutions, support client decision-making, and contribute to business generation and people development.

Build and maintain high-performance market data infrastructure in Rust to ingest, process, store, and serve real-time pricing feeds. Solve latency, data quality, and cross-exchange consistency problems, contribute trading/market-data expertise to engineering decisions, communicate with a distributed team, and potentially lead a small team over time.

Design and implement scalable features, build data pipelines, collaborate with cross-functional teams, and enhance data infrastructure for improved decision-making.

The Senior Data Engineer will build and maintain data pipelines, distributed ETL/ELT workflows, and data storage systems while collaborating with various teams to optimize data quality and performance.

The Software Engineer will enhance the data ingestion pipeline, collaborating with scientists for model training and data optimization, while managing cloud infrastructure.

Lead Finance data engineering: own end-to-end pipelines for financial and regulatory processes (IFRS 17), ensure scalability, auditability, quality and governance, design large-scale processing, document lineage and models, provide hands-on technical leadership, mentor engineers, and collaborate with finance, actuarial, risk and AI stakeholders to evolve data engineering practices for analytics and AI.

Build and operate the data and ML platform for non-invasive neural interfaces: ingest, version, process, and serve large-scale neural data; create dataset pipelines, distributed training, experiment tracking, model deployment, and tooling; manage cloud and GPU compute; improve data quality, metadata, monitoring, and reproducibility; collaborate with ML engineers, neuroscientists, software engineers, and product teams.