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Data Engineer GCP at Talan, a tech consulting group: develop and maintain big data use cases for major clients on Google Cloud (compute, storage), model and secure cloud data, and run POCs, benchmarks, and internal training. Requires 3+ years on data projects with GCP exposure and a language like Python, Scala, Spark, Java, or R.
DevOps production engineer providing level-3 production support embedded at a large investment bank in Paris, helping build a private PaaS cloud. Day to day: deploying middleware infrastructure, automating deployments with Ansible/Ansible Tower, CI with Jenkins, and running high-availability production on Docker, Big Data/NoSQL, with Oracle, SQL Server, Sybase, MongoDB.
Build & Run DevOps engineer in Neurones' managed-services division: coordinates the technical roadmap, ensures application reliability on Red Hat Linux, and contributes to monitoring and performance optimization in close collaboration with project and production teams.
Talan is hiring a GCP Data Engineer to help business units evaluate process efficiency and optimize performance through Big Data use cases on Google Cloud Platform. Joining the Tech For Data team in Paris, you'll work on projects for major clients in luxury/retail and banking/insurance.
Design and maintain data pipelines for genomic and clinical data used in oncology research, building the infrastructure and scripts to process large volumes in a secure, compliant environment. Core stack includes SQL, Python/Scala, Airflow, and Kubernetes.
Data engineer on Neurones SA's Paris-based data team, supporting clients' data initiatives: scoping needs, collecting and cleaning data, running exploratory analysis, and building reports and dashboards. Also deploys decision-support (BI) tools and provides user support to drive adoption.
Experienced data engineer designing, building and industrializing data pipelines for an insurance brokerage group's internal data platform: dbt transformations, Airflow DAGs and Python ingestion on a Bronze/Silver/Gold Lakehouse (Trino/Starburst, Iceberg, OpenMetadata), delivering reliable documented datasets to BI (Power BI, Metabase, SuperSet) and business teams.
Data Engineer consultant at Act-On Data builds and industrializes data pipelines for large clients: collecting/integrating data on-premise or cloud, cleaning, transforming and modeling datasets with Python and SQL, ensuring quality and automating flows to production in Agile teams alongside analysts, data scientists and client IT teams.
Senior data engineer on a client data-platform team, collecting and centralizing heterogeneous data sources while ensuring security, compliance, and governance. Day-to-day work is building scalable pipelines and infra with Python, Spark, SQL, Airflow, Delta Lake, GCP (BigQuery, Dataproc, PubSub) and Terraform/Terragrunt.
Lead Data Engineer at Sancare (Paris, Châtelet), a ~40-person company applying AI to hospital health data. You own and evolve the production data platform (dbt, Dagster, ClickHouse, S3, PostgreSQL), fix performance/reliability issues, standardize data engineering practices, and ensure GDPR/HDS compliance.
DevOps/production engineer (CDI) at Consort Group piloting OPS projects and production reliability for a payments & cash-management (monetics) division — integrating apps, running cloud migrations, and handling incidents and monitoring — using Linux, Kubernetes/OpenShift, Terraform, Oracle/PostgreSQL, Kafka and Dynatrace/Grafana.
Senior DevOps engineer at Codebusters, sent on client missions to build financial computation engines (risk, PnL, XVA, FRTB), migrate legacy systems to cloud, and industrialize CI/CD on critical platforms. Core stack: C# or Java with TDD/clean code, CI/CD tools (Azure DevOps, GitLab CI, GitHub Actions, Jenkins), Linux, with Terraform/Azure/AWS as bonus.
10-month freelance AI & Data Engineer mission in Paris (Saint-Denis, hybrid with 2-3 remote days/week) via recruiter Hanson Regan, on a Data Analytics & AI team. Day to day: build ML/LLM solutions with TensorFlow/PyTorch, run MLOps with MLflow, CI/CD, Docker/Kubernetes, Terraform, plus data modeling/governance and warehouse work.
Olga Pakhomova - Mercato de l'Emploi cherche un Data Engineer confirmé pour piloter l'intégration et la gestion des flux EDI et B2B. Vous travaillerez sur l'automatisation et l'industrialisation des…
Builds and industrializes end-to-end data pipelines (including HR analytics) for Act-On Group's large clients, working with Data Analysts, Data Scientists and IT teams on-premise and in the cloud. Core stack: Python, SQL, cloud platforms (Azure/AWS/GCP) and tools like Databricks, Talend, SSIS and Alteryx.
Permanent (CDI) DevOps engineer role in Élancourt, France, deploying and supporting a secure messaging, geolocation and video-call solution for intervention services at a defense-sector client. Day-to-day: build and maintain Ansible/GitLab CI pipelines for Kubernetes cluster deployment, and run/support step-CA certificates, AI servers and TrueNAS storage in an international team.
Consulting role (via BTI-Advisory) placed with a large luxury group in Paris: the engineer administers Azure and GCP access under least-privilege policies, deploys compliance rules with Terraform/Terraform Cloud, manages permissions in GitLab and Dynatrace, and automates operations with Python, PowerShell, and Bash while supporting production teams and maintaining runbooks.
DevOps engineer at STET, a European interbank payment processor, designing automated CI/CD deployment pipelines, maintaining Linux/container infrastructure, and supporting internal dev teams and production (level 2). Core stack: Linux, container orchestration, Git/Ansible/Jenkins/Puppet, Bash/Shell/Python scripting, and AWS.
DevOps engineer (PHP/MVC) to join a technical project at a large corporation in Paris, with two days per week working from home. The core requirement is PHP/MVC experience; the posting offers a permanent contract title while describing a 90-day mission starting 25/11/2025.
The United Nations Environment Programme (UNEP) in Paris is seeking a Remote Sensing Data Engineer consultant to ensure a reliable flow of satellite detections into MARS from existing and newly integrated data sources.…
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