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Consultant builds and optimizes data pipelines on Databricks for clients, designing scalable Spark-based solutions and advising on architecture improvements.
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.
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.
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.
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 and maintain BI/Big Data pipelines: ETL with Talend/Informatica, Spark processing, and Python/Scala analytics to deliver reports and dashboards for business insights.
Build and maintain modern data pipelines using Spark and Scala on GCP to modernize legacy data platforms.
Designs and builds Azure-based data pipelines and FinOps dashboards using Spark and Scala to track expenses and ensure data quality for AXA’s finance teams.
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.
Migrate and automate data pipelines from Cloudera Hadoop to Databricks, using Python (PySpark), SQL, Airflow, and Azure DevOps for CI/CD.
Builds and maintains robust data pipelines for financial institutions, collecting and transforming data for analytics and regulatory compliance using Python, SQL, and cloud platforms.
Data Engineer builds and maintains scalable data pipelines, integrates diverse sources, and ensures data quality for clients and internal projects using Python, Spark, and cloud platforms.
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.
Build and optimize data pipelines on AWS for clients, focusing on automation, Spark, and CI/CD to enable scalable analytics and business insights.
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.
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.
Design and maintain scalable data pipelines and architectures (ETL/ELT, data lakes, warehouses) using Python, SQL, Spark, Kafka, and cloud platforms (AWS/GCP/Azure).
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