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Senior Data Engineer: Big Data, Spark & Cloud Platforms
Designs, builds, and maintains high-volume big-data pipelines using Java/Spring, Spark, and Hadoop in a cloud environment, with TDD/BDD and automated deployments.
Data Engineer AWS – Data Platform / IA (H/F)
Build and maintain AWS-based data pipelines and lakehouse architecture for a large bank’s AI and ESG initiatives, using PySpark, Java, and CI/CD.
Alternance – Data Engineer – Services Financiers – Data factory -Nantes
Alternant Data Engineer in Sopra Steria’s Data Factory, building and optimizing Big Data pipelines for financial clients using Spark, Python, SQL, and cloud tools like Databricks and Snowflake.
Tech Lead Data Engineer H/F
Leads data engineering squads building scalable data pipelines and ML-ready architectures for enterprise clients using Spark, Kafka, and cloud platforms like Azure Databricks and AWS.
Senior Data Engineer — Big Data Architect, Cloud & AI
Design and build robust, high-performance Big Data pipelines and ETL modules using SQL, Python, Snowflake, Databricks, Hadoop and Kafka in a Cloud environment.
Data Engineer – H/F CDI - Paris
Build and maintain data pipelines, clean and model customer data, and deploy BigData solutions on AWS/Azure for a product-focused team.
Data Engineer Senior Big Data & Cloud (IT) / Freelance
Build and scale high-volume data pipelines and cloud-native data platforms using Java/Spring, Spark, Hadoop, and AWS/Azure for a consulting client.
Data Engineer - Hadoop Cloudera & Big Data Automation
Maintain and automate a Cloudera Hadoop CDP Big Data platform, handling cluster administration, upgrades, incident resolution, and infrastructure-as-code deployments.
Data Engineer Spark Confirmé (H/F)
Build real-time customer 360 data pipelines and modernize a big-data stack (Spark, Kafka, Hadoop Cloudera) for a major bank’s marketing analytics and digital products.
Data Engineer F/H migration Databricks
Migrate and automate data pipelines from Cloudera Hadoop to Databricks, using Python (PySpark), SQL, Airflow, and Azure DevOps for CI/CD.
Data Engineer confirmé(e) - Assurance - Lille
Builds and maintains secure, scalable data pipelines for insurance clients using ETL/ELT tools, cloud platforms, and distributed processing frameworks like Spark and Kafka.
Tech Lead Data Engineer / Cloud Architecte
Leads the design and rollout of a secure, governed data and AI platform for a major media/public-sector client, integrating GCP/AWS, Kubernetes, Kafka, and Collibra with strict data-security and DevOps practices.
Consultant.e Data Engineer AWS H/F
Build and optimize data pipelines on AWS for clients, focusing on automation, Spark, and CI/CD to enable scalable analytics and business insights.
Remote Data Engineer - Spark, Scala & Snowflake
Build and maintain high-performance data pipelines using Scala and Spark, migrating legacy Hadoop systems to Snowflake for Groupe Open’s Open Data & AI unit.
Data Engineer / Data Analyst confirmé à expert (F/H)
Build and maintain cloud data pipelines and analytics for banking/insurance clients using Spark, Kafka, AWS, and Python, with a focus on data quality and risk/finance reporting.
Data Engineer Cloud Azure F/H
Designs and runs Azure-based big-data pipelines using Spark, Hadoop, and Azure services to ingest, process, and store data for analytics and AI projects.
Data Engineer senior – Databricks (H/F)
Design and maintain scalable data pipelines on Databricks using Spark, Python, Scala, and SQL to collect, store, and process large volumes of data for analytics and AI workloads.
Data Engineer Junior (H/F) - Alternance
Build and maintain data pipelines and databases to collect, transform, and deliver data for analytics and reporting under supervision.
Data Engineer confirmé(e) - Assurance - Lille
Build and maintain robust, secure data pipelines for insurance clients using ETL/ELT tools, distributed processing (Spark/Hadoop), and cloud platforms to deliver reliable data for business use cases.
Data Engineer Microsoft AZURE Montreuil CDI
Designs and builds cloud-based data pipelines and analytics platforms on Microsoft Azure or GCP, using ETL tools, SQL, Python/Java/Scala, and data-lake architectures to deliver business insights.