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Build and maintain scalable data pipelines on Azure and Microsoft Fabric, from ingestion to analytics, using Azure Data Factory, Synapse, and Fabric components.
Senior Data Engineer role using Dataiku to design data pipelines, build visualizations, and advise clients on AI/ML solutions with Python, Spark, and cloud platforms.
Build and optimize data pipelines, analyze business needs, and deliver visualizations using Dataiku, Python, and Spark to drive AI-driven solutions for clients in finance, healthcare, mobility, and climate sectors.
Builds and maintains Snowflake-based data pipelines for banking clients, ensuring data quality and reliability using Python, PySpark, SQL and CI/CD.
Designs and maintains scalable GCP data pipelines (BigQuery, Dataflow, Dataproc) for retail clients, automating data flows and optimizing analytics infrastructure.
Build and maintain data pipelines for a media company using Python and PySpark, with autonomy and mentorship.
Build and maintain a unified data platform on Azure and Microsoft Fabric, designing end-to-end ETL/ELT pipelines and analytics workflows.
Build and maintain ML pipelines for banking use-cases, deploy models to production, and monitor performance using Python, Spark, Kubernetes, and AWS SageMaker.
Build and deploy data pipelines and cloud infrastructure on AWS for an energy-sector client, enabling trading, analytics, and sustainability use cases with PySpark, Databricks, and Python.
Senior Data Engineer building and optimizing data pipelines and warehouse models for Ubisoft’s Publishing domain, using SQL, Python, PySpark, Snowflake, and Databricks.
Build and maintain a PySpark-based data pipeline and DataLake for a finance company, including ingestion, CI/CD, and data structuring.
Build and maintain scalable ETL/ELT pipelines on Databricks (Spark SQL, PySpark, Scala) to feed reliable, high-performance data for analytics and decision-making.
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 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.
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.
Build and maintain Snowflake-based data pipelines for banking clients, ingesting and transforming data with Python/PySpark and CI/CD tooling.
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.
Build and maintain data pipelines, clean and model customer data, and deploy BigData solutions on AWS/Azure for a product-focused team.
Build and optimize ETL/ELT pipelines on Databricks using Spark SQL, PySpark, and Scala, and set up a Lakehouse with Delta Lake for reliable, secure data delivery.
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