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Build and optimize Azure-based data pipelines, warehouses, and analytics for Global Wealth and Asset Management using Databricks, Synapse, and Power BI.
Principal Data Engineer builds and scales Azure-based data pipelines, lakes, and analytics platforms using Databricks, PySpark, and Azure services to deliver governed data solutions for clients.
Lead a team building and scaling Azure Data Factory and Databricks pipelines in Brampton, handling ingestion, transformation, and loading while ensuring data quality and security.
Designs and builds scalable data pipelines and lakehouse architectures on Azure/Databricks to power analytics and ML, using ELT/ETL, star/snowflake schemas, and streaming/event-driven patterns.
Build and maintain Azure-based data pipelines, warehouses, and analytics solutions using Data Factory, Power BI, and GenAI to deliver real-time insights for enterprise clients.
Builds and maintains Azure-based data pipelines and lakehouse/warehouse solutions using Databricks, PySpark, and Microsoft data stack to power analytics and applications.
Build and maintain scalable data pipelines in Databricks for a financial client, using PySpark, Azure, and medallion architecture to process batch and streaming data.
Designs and builds Azure-based data pipelines and models, turning business needs into scalable, analytics-ready data products for BI and reporting.
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.
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