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Builds and optimizes a cloud-based manufacturing data lake using AWS services, Python, and SQL to support data-driven decision-making.
Designs and maintains data pipelines to feed manufacturing analytics, curating data in a lake and enabling BI insights for factory automation.
Leads data engineering initiatives, migrates systems to Azure Databricks, and guides the team on Python, ETL, and data architecture best practices.
Build and maintain large-scale data pipelines using Azure Databricks, Spark, and PySpark, optimizing performance for TB-scale processing and collaborating with cross-functional teams.
Build and maintain large-scale data pipelines using Azure Databricks, PySpark, and SQL to process TB-scale datasets for a multinational insurance provider.
Build and optimize large-scale data pipelines using Scala, Python, PySpark, and Databricks on Azure, designing cloud-native data architectures for enterprise clients.
Design and maintain Azure-based data pipelines for a Microsoft Fabric-powered lakehouse, integrating utility and IoT data for analytics and reporting.
Design and build AWS-based data platforms, including data lakes, warehouses, and pipelines, while providing architectural oversight and ensuring security and cost optimization.
Build and maintain scalable data pipelines on Azure Databricks using PySpark and SQL, enforce governance with Microsoft Purview, and integrate analytics via Microsoft Fabric.
Designs and implements real-time data replication pipelines using Qlik Replicate, CDC, and hybrid cloud architectures to keep analytics platforms synchronized.
Lead the design and optimization of scalable Azure data pipelines using Databricks, PySpark, and ADF, while mentoring engineers and collaborating with cross-functional teams.
Build and scale a cloud-native data platform on AWS to power real-time recommendations and analytics for Europe’s leading brands.
Build and maintain data pipelines for trade and communications surveillance, ensuring regulatory compliance and data quality across AWS infrastructure.
Build and maintain cloud-native AWS data platforms, ETL/ELT pipelines, and data lakes to support analytics and BI use cases.
Build and maintain scalable ETL pipelines using Azure Data Factory, Synapse, Databricks, and Spark to process and optimize data solutions.
Lead a team of data engineers to design, build, and optimize cloud-based data pipelines and warehouses using Python, SQL, Spark, and cloud platforms like Azure or AWS.
Build and maintain Azure-based data pipelines and Power BI reports for clients, troubleshooting issues and mentoring junior engineers using Microsoft’s data stack.
Builds and maintains scalable ETL pipelines on Databricks and AWS to turn raw data into clean, analytics-ready datasets for reporting and business insights.
Builds and maintains enterprise data pipelines and analytics platforms using SQL, ETL/ELT, and cloud tools like Microsoft Fabric to support reporting and AI initiatives.
Builds and maintains data pipelines and analytics infrastructure for a semiconductor manufacturer, enabling reliable data access for BI and data science teams.
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