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Lead a team migrating legacy data systems to a modern Databricks/Azure platform, building scalable batch and streaming pipelines, and deploying BI, ML, and GenAI use cases for a large financial client.
Senior Python engineer building scalable data pipelines and applications to modernize energy-sector systems using Python, Pandas, and DevOps practices.
Build and maintain scalable data pipelines on Databricks, collaborating with cross-functional teams to deliver robust data architectures.
Design and deploy modern data analytics solutions on Microsoft Azure and Fabric, building ETL pipelines and optimizing data models for BI insights.
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.
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.
Build and maintain cloud-based data platforms (datalakes, ETL pipelines) for enterprise clients, using AWS/GCP/Azure, Python, Airflow, and DevOps tools.
Builds and maintains Power BI dashboards and standardizes reporting for AXA’s business units, ensuring data accuracy and supporting quality audits.
Consultant builds and optimizes cloud data pipelines on GCP for enterprise clients, blending Data engineering and BI to support digital transformations.
Build and maintain cloud-based ETL pipelines using Azure/AWS and Python, ensuring reliable data flows for analytics and reporting.
Build and deploy Microsoft-based data pipelines and cloud solutions for clients, focusing on Azure data services and AI/ML integrations.
Senior Data Engineer designing and building cloud data pipelines and warehouses on GCP using BigQuery and Dataflow for a consulting team.
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.
Lead a data engineering team to build robust Python and Spark-based data pipelines and infrastructure, leveraging PostgreSQL and guiding technical decisions in a hybrid work setup.
Architect and build robust data pipelines using Python, SQL, and Airflow for an AI-driven data platform in a new agency setting.
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.
Build complex BI reports and run advanced SQL queries while rewriting a legacy application in Clermont-Ferrand.
Senior Data Engineer to industrialize analytics and ML use cases using Databricks in an Agile environment, turning prototypes into robust solutions.
Design and build scalable data pipelines and cloud-based ETL workflows to collect, store, and reliably deliver business data for analytics and decision-making.
Builds ETL pipelines, integrates data sources, and creates Power BI dashboards in a cloud-based BI environment using Python and GCP/AWS.
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