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Data Engineer Databricks confirmé - H/F - CDI
Build and optimize end-to-end data pipelines on Databricks and Spark, integrating real-time and batch data for analytics and AI use cases.
Tech Lead Data Engineer H/F
Lead a team to design, build, and maintain robust data pipelines and architectures for enterprise clients, using SQL, Python/Java/Scala, Kafka, and cloud/big-data stacks.
Data Engineer Confirmé Databricks - F/H
Build and maintain scalable ETL/ELT pipelines on Databricks (Spark SQL, PySpark, Scala) to feed reliable, high-performance data for analytics and decision-making.
Data Engineer Senior Scala / Spark / Databricks
Senior Data Engineer builds and optimizes large-scale data pipelines using Scala, Spark, and Databricks, then delivers BI reports in Power BI for a French enterprise data factory.
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.
Senior Cloud Data Engineer (H/F)
Build and maintain cloud-based data platforms (datalakes, ETL pipelines) for enterprise clients, using AWS/GCP/Azure, Python, Airflow, and DevOps tools.
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.
Data Engineer Python/AWS (F/H)
Build and maintain distributed data pipelines and cloud services using Python, PySpark, and AWS (Glue, Lambda, ECS) to deliver reliable, high-performance data APIs and integrations.
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.
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.
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 Informatica IDMC (H/F)
Build and maintain robust data pipelines and warehouses using Informatica IDMC, Python, SQL, and Google Cloud, enabling analytics and future AI models for a cooperative sector leader.
Data Engineer Confirmé Databricks - F/H
Build and maintain scalable ETL/ELT pipelines on Databricks using Spark SQL, PySpark, and Scala to feed reliable, high-performance data for analytics and decision-making.
Data Engineer GCP (H/F)
Build and maintain scalable ETL/ELT pipelines on Google Cloud Platform, optimize BigQuery warehouses, and automate data workflows with Python, SQL, and Terraform for real-time analytics and business insights.
Data Engineer Modern Data Stack F/H
Build and maintain cloud-based data pipelines in Python and SQL, design modern data platforms (Data Lake, Warehouse), and ensure data quality and observability for analytics and AI projects.
Data Engineer - Build Robust Data Solutions & Governance
Designs and deploys robust data pipelines and governance frameworks, using SQL and Python/Java/Scala with distributed compute and CI/CD tooling.
Data Engineer Modern Data Stack F/H
Build and maintain cloud-based data pipelines in Python/SQL, design modern data platforms (Azure/AWS/GCP), and ensure data quality and observability for analytics and AI projects.
Data Engineer Senior F/H
Senior Data Engineer designs, builds, and maintains scalable data pipelines and architectures for clients, using Spark, Python, Kafka, and Hadoop to ensure reliable data collection, storage, and processing.
Lead Data Engineer F/H
Lead Data Engineer designs, builds, and maintains scalable data pipelines and distributed processing systems using Spark, Scala, and Java to enable analytics and model monitoring for clients.
Data Engineer / DataOps (H/F)
Designs, builds, and maintains scalable data pipelines and streaming architectures using Spark, Kafka, and Python, while enforcing data quality, observability, and CI/CD practices for enterprise clients.