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Design and operate data pipelines that transform healthcare reference data into reliable datasets for SaaS products using Python, Spark, and AI agents; collaborate on AI-native features and partner integrations.
Build and deploy end-to-end ML systems—from data pipelines to production models—using Python and libraries like Pandas, Scikit-learn, and PyTorch.
Build and maintain scalable ETL/ELT pipelines and analytics-ready datasets using Databricks, dbt, and SQL, ensuring data quality and reliability for business insights.
Builds and maintains Databricks-based data pipelines that feed IT performance metrics into an Operational Data Store, using PySpark/Scala/SQL and Medallion architecture for real-time Power BI dashboards.
Designs and scales cloud-based data infrastructure for electric vehicles, focusing on multi-region Databricks orchestration and Terraform-driven IaC to support analytics and software-defined vehicle systems.
Design and deploy production-grade Databricks platforms for enterprise clients, leading end-to-end cloud data engineering projects on AWS/Azure.
Design and build scalable data platforms on Microsoft Fabric and Azure using PySpark and SQL, integrating enterprise sources for advanced analytics and reporting.
Build and maintain data pipelines in Azure to power Sales and Finance reporting dashboards for a global consumer-products company.
Builds and scales a Lakehouse data platform using PySpark, Databricks, Azure services, and ELT pipelines to power analytics and AI workloads.
Designs scalable data systems and ETL pipelines using Python, Airflow, BigQuery, and PySpark to support analytics and business operations.
Build and own ML models for marketing at a BNPL fintech, including customer intent modeling, next-best-action frameworks, and marketing mix modeling to drive customer acquisition and budget allocation.
Build and scale a unified data ecosystem for 60+ brands using Databricks, SQL, and cloud pipelines to power analytics and AI across Europe.
Build and maintain data pipelines and flows in Dataiku DSS for banking clients, focusing on ingestion, quality, and CI/CD while collaborating with cross-functional teams.
Build and maintain scalable data pipelines on Databricks and AWS for JPMorgan’s enterprise analytics and AI/ML workloads using Python, PySpark, and SQL.
Lead a team building scalable data pipelines and warehousing on AWS for HR analytics, using PySpark, Kafka, and Terraform to integrate disparate systems and deliver business intelligence.
Lead a team building scalable data pipelines and warehousing solutions on AWS for HR analytics, using PySpark, Kafka, and Terraform to integrate disparate systems and deliver business intelligence.
Maintains and troubleshoots Azure Databricks, CI/CD pipelines, and Power BI services, ensuring data workflows and dashboards stay operational.
Principal Data Engineer at Microsoft CoreAI designs and owns global data/analytics foundations for AI platforms, building scalable pipelines and governance to power AI-driven products.
Design and build scalable data pipelines for vehicle signals and diagnostics using Databricks, PySpark, and Azure to deliver production-grade data solutions.
Designs and builds scalable data pipelines and products using Databricks, PySpark, and Azure to process vehicle signals, diagnostics, and customer feedback for mobility/logistics systems.
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