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Builds scalable data pipelines and AI/ML models, including LLM-based solutions, to detect financial crime for a UK banking client using Python, PySpark, and Big Data tools.
Build scalable data pipelines and AI/ML models for anti-financial crime at a UK bank, using Python, LLM frameworks, and distributed computing on GCP.
Build and maintain scalable data pipelines and Lakehouse architectures using Databricks, PySpark, and Delta Lake to power analytics and GenAI solutions for enterprise clients.
Senior Data Engineer builds and maintains scalable data pipelines and lakehouse platforms using Databricks (Spark, Delta Lake), Python, and SQL to support anti-financial-crime analytics for PwC’s global clients.
Design and build a modern data platform on Databricks and Azure, developing scalable ETL/ELT pipelines with Python and PySpark to integrate data sources for AI-assisted development.
Design and build scalable Lakehouse architectures (Bronze/Silver/Gold) using Databricks and Delta Lake to transform logistics data into BI insights, optimizing ETL/ELT pipelines with PySpark and Azure/AWS/GCP services.
Design and optimize scalable data pipelines using Databricks, Apache Airflow, and Spark to process streaming and batch data for enterprise clients across industries like aerospace, energy, and automotive.
Designs and builds cloud data pipelines on Azure Databricks, integrating PySpark, Delta Lake, and Azure Data Factory to power analytics and BI for enterprise clients.
Build and maintain scalable data pipelines using PySpark, Hadoop, and Airflow in a DevOps environment, collaborating with analysts and engineers to deliver high-performance solutions.
Build and maintain scalable data pipelines and lakehouse platforms using Databricks, Spark, Delta Lake and Azure to support anti-financial-crime analytics and reporting for PwC’s global clients.
Build and maintain scalable data pipelines and Lakehouse models on Databricks, using PySpark, Delta Lake, and Medallion architecture to deliver analytics-ready datasets for enterprise clients.
Build and maintain cloud-based data pipelines and Lakehouse architectures using Azure, AWS, Databricks, and PySpark to deliver clean, scalable data for analytics and AI teams.
Lead a data engineering team to migrate and modernize a media company’s data platform on GCP using PySpark, while removing technical bottlenecks and guiding architectural decisions.
Lead a team to design and build scalable Azure data pipelines and warehouses using Databricks, PySpark, and SQL to process large datasets for enterprise clients.
Build and maintain scalable Azure data pipelines and lakehouse solutions using Databricks, PySpark, and Azure Data Factory to process and transform large datasets for enterprise clients.
Build and maintain scalable Azure data pipelines and Databricks lakehouse solutions, transforming raw data into analytics-ready assets while collaborating with cross-functional teams.
Build and optimize a modern data platform on Databricks and Azure, designing scalable ETL/ELT pipelines and integrating data from Delta Tables and Event Hub using Python and PySpark.
Designs and migrates enterprise data pipelines using Informatica and Microsoft Azure tools, blending ETL/ELT with cloud analytics and AI services.
Design and build ETL/ELT pipelines using Informatica and Microsoft Azure tools, migrating enterprise data to cloud-based Microsoft Fabric and integrating AI services like Azure OpenAI.
Build and maintain scalable data pipelines and lakehouse platforms using Databricks, Spark, Delta Lake, and Python to support anti-financial-crime analytics and reporting for global PwC clients.
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