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Senior Data Engineer builds and scales Databricks/AWS pipelines to industrialize analytics and ML prototypes into robust, governed solutions for an energy-sector platform.
Design and build large-scale data pipelines on Azure/Databricks using PySpark, ensuring quality and performance for a major electricity distributor.
Senior Data Engineer designing and building scalable data pipelines on Microsoft Fabric and Azure, using Python/PySpark, SQL, and Power BI to deliver analytics solutions for enterprise clients.
Designs, builds, and maintains scalable data pipelines and cloud-based data platforms for financial clients, using AWS, Databricks, Airflow, dbt, PySpark, and CI/CD.
Build and maintain data pipelines, clean and model customer data, and deploy scalable BigData solutions on AWS/Azure for marketing analytics.
Designs, builds, and deploys distributed data pipelines using Python, PySpark, and AWS services for clients.
Builds and maintains Azure data pipelines using Data Factory, Synapse, PySpark, and Power BI to process and analyze enterprise data.
Build and maintain data pipelines and transformations for a SaaS platform serving automotive manufacturers and dealers, using dbt, Python, SQL, AWS S3/Redshift, and Parquet.
Senior Data Engineer building and maintaining a modern Lakehouse data platform using Databricks, Airflow, and PySpark pipelines with a focus on data governance and lineage.
Build and maintain data pipelines in Microsoft Fabric, model insurance-brokerage data, and deliver clean datasets for BI, analytics, and regulatory reporting.
Design and build scalable data pipelines and cloud-based data platforms using PySpark, Snowflake, and Databricks to support AI and analytics initiatives.
Build and maintain scalable data pipelines on Microsoft Azure and Databricks using PySpark, SQL, and CI/CD, while collaborating with cross-functional teams to deliver end-to-end data solutions.
Design and deploy large-scale data pipelines on Azure Databricks using PySpark, evolving the data architecture for a major ESN client.
Build and maintain scalable data pipelines using Python, SQL, Spark, and cloud services (Azure/AWS/GCP) to deliver clean, reliable datasets for analytics and AI teams.
Build and optimize scalable data pipelines on Databricks and cloud platforms, transforming raw data into automated, production-ready analytics and AI infrastructure using Python, Spark, and IaC.
Designs and maintains scalable cloud-based data pipelines and storage using Python, SQL, and cloud platforms like Azure/AWS/GCP to ensure reliable, high-quality data for business operations.
Build and maintain scalable data pipelines in Python/PySpark on AWS to ingest, transform, and expose market data for anomaly detection in a fintech setting.
Build and maintain scalable data pipelines on Microsoft Fabric, optimizing performance and ensuring data quality for Groupe Premium.
Build and scale a cloud-native data platform on AWS, driving real-time analytics, personalization, and AI-powered data products for millions of users.
Build and maintain ETL/ELT pipelines in Python and Spark/Scala to transform healthcare reference data into reliable datasets for SaaS products and partners, while collaborating with AI engineers and product teams.
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