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Designs and builds scalable data pipelines and Lakehouse/Data Warehouse solutions on Microsoft Fabric and Azure for analytics and AI workloads.
Design and build scalable data pipelines and Lakehouse/Data Warehouse solutions using Microsoft Fabric, Azure Synapse, and Databricks to enable analytics and AI workloads.
Design and evolve a Databricks Lakehouse platform for an AI-first company, defining Medallion layers, Unity Catalogue governance, and compute optimizations to power large-scale AI workloads.
Design and evolve a Databricks Lakehouse platform, owning architecture and modern data foundations with Databricks, Delta Lake, Unity Catalogue, Python, SQL, and PySpark.
Design and advise on Microsoft-based Data & AI solutions, guiding customers through analytics, AI, and data-platform modernization using Azure, Fabric, and Power BI.
Build and maintain real-time data pipelines using CDC, Kafka, Spark, and Iceberg to move and transform enterprise data across Bronze-Silver-Gold layers.
Builds AWS-based cloud-native backend services and data pipelines using TypeScript, Lambda, and Terraform to ingest and process automotive production alarm data for a global manufacturer.
Build and demo AI-powered data solutions for Fortune 500 clients, turning raw enterprise data into production-ready semantic layers and agent-facing products within days.
Build streaming and batch data pipelines, govern contracts, and design a scalable lakehouse to power trading desks and asset management with reliable, observable data services.
Build and optimize Databricks Lakehouse pipelines on AWS/Azure, set CI/CD standards, and mentor peers while integrating structured and unstructured data with Delta Lake and Unity Catalog.
Builds the data platform foundation for an AI analytics startup, enabling trustworthy answers from enterprise data without heavy schema migrations or data movement.
Principal Data Engineer designs and builds secure, scalable data platforms for national-scale genomics and healthcare research, using Python, SQL, and cloud infrastructure.
Leads the design of enterprise-scale data platforms, cloud solutions, and governance standards to modernize and secure the data landscape for a data-driven organization.
Build the data foundation for an AI analytics platform that delivers trustworthy answers from enterprise data without heavy schema migrations or data movement.
Architect and lead the enterprise AI stack for a diversified investment group, selecting platforms, MLOps, and cloud infrastructure to scale secure AI adoption across portfolio companies.
Design and build modern data solutions on Microsoft Fabric and Azure, using Lakehouse, Warehouse, Notebooks, and Spark pipelines for large-scale datasets.
Lead a team building and operating cloud-native data platforms on AWS to power AI/ML and analytics, using Python/Node.js, CI/CD, and IaC while ensuring security and cost efficiency.
Designs and builds cloud-based ELT/ETL pipelines on AWS/Azure and Databricks to integrate financial, ERP, and operational data for a renewable-energy IPP, then delivers Power BI reports for executives and investors.
Build and operate PayPay’s AWS-based data infrastructure using Terraform and Databricks, ensuring reliability, security, and smooth data workloads for the fintech platform.
Designs and builds end-to-end data pipelines on Azure Synapse and Data Factory, modeling relational/ dimensional data and ensuring quality, governance, and CI/CD for enterprise clients.
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