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Design and build scalable cloud data pipelines and lakehouse architectures using Microsoft Fabric and Azure, enabling clients to turn raw data into actionable intelligence through end-to-end data engineering.
Builds and maintains data pipelines and analytics-ready datasets in Snowflake and Power BI for large capital-infrastructure programs, using Azure Data Factory to ingest and transform messy data from ERP, PMIS, and external sources.
Build and maintain scalable data pipelines and infrastructure to support analytics, reporting, and AI initiatives for Teladoc Health Canada’s virtual care platform.
Lead a team to design and build scalable data platforms, ETL/ELT pipelines, and AI-enabled solutions on Azure and on-premise, supporting Ethoca’s fintech payments infrastructure.
Leads a team building scalable data platforms on Azure/AWS, using Spark, Hadoop, and Airflow to power enterprise analytics and AI solutions.
Designs and maintains data pipelines and infrastructure to ingest, transform, and validate healthcare data for analytics and AI initiatives, using tools like Talend, Python, and Power BI.
Build and maintain an AI-forward data platform using Databricks, Python, PySpark, and cloud services to power analytics and ML for life-sciences clients.
Lead enterprise cloud modernization and platform engineering efforts using Azure, GCP, Kubernetes, and Terraform to design and automate scalable DevOps pipelines.
Design and modernize a cloud data platform on Azure, migrating legacy MSBI systems to a Medallion Architecture and building Data Products for end-to-end data flows.
Build and optimize both applications and data pipelines using Java, Python, JavaScript, and ETL tools to deliver scalable solutions.
Design and build scalable data pipelines and infrastructure to ingest, process, and transform large volumes of data using modern cloud and big-data tools.
Build and optimize a modern cloud-first data ecosystem for a fintech retailer, using Azure, Databricks, and PowerBI to create analytics and reporting solutions that drive operational efficiency and compliance.
Build and maintain Databricks-on-Azure pipelines and dashboards that turn industrial manufacturing data into KPIs and insights for R&D, quality, and production teams.
Build and maintain data pipelines and infrastructure to support AI model training and analytics at a company whose core product is AI.
Designs and maintains the data infrastructure for an AI company, ensuring scalable pipelines and efficient data models.
Designs and governs an Azure-based data platform, migrating legacy systems to modern cloud architectures and leading data product development.
Designs and maintains ETL pipelines and data warehouses for an aerospace industry client, integrating ERP data and building finance-focused datamarts.
Lead a team building and scaling Azure-based data pipelines and AI-ready data models for a large ecommerce retailer using PySpark, Databricks, and Data Factory.
Build and maintain robust ETL pipelines, cloud data platforms, and databases to ensure high-quality data for analytics and AI teams using Python, Spark, and cloud services like AWS/Azure/GCP.
Build and maintain data pipelines on Microsoft Azure and Fabric, using PySpark, Python, and SQL to move and transform customer data for analytics and BI solutions.
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