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Builds scalable data pipelines and analytics using Microsoft Azure, Fabric, and Quantexa for financial and regulatory clients.
Build and maintain scalable data architectures using Azure, Fabric, and Quantexa, developing pipelines, APIs, and analytics for financial and regulatory use cases.
Design and operate Microsoft Fabric-based data platforms, building scalable ETL/ELT pipelines in Python and PySpark to support clean-energy infrastructure analytics.
Builds and optimizes cloud-based data pipelines and architectures using Databricks, Snowflake, and Microsoft Fabric to deliver reliable, scalable data solutions for analytics and AI.
Designs and builds scalable Azure data pipelines using Databricks and Data Lake Storage, leveraging Python/Scala to enable analytics and cloud-native data solutions.
Build and maintain Dataiku and Snowflake-based data platforms using Python, SQL, and DataOps to deliver governed AI and analytics for internal teams.
Designs and builds end-to-end data pipelines, cloud data platforms, and automated ELT processes for clients, ensuring scalable, secure, and high-quality data architectures.
Principal Consultant leads the Data Engineering team, designing scalable data pipelines, warehouses, and cloud platforms using Python, Spark, SQL, and Azure/AWS/GCP to deliver end-to-end data solutions for enterprise clients.
Build and maintain cloud-based data pipelines and architectures for analytics and AI workflows in a consultancy role, primarily remote with occasional on-site client work.
Build and maintain scalable Azure-based data pipelines and ETL processes to support reporting, analytics, and AI use cases for a Dutch income-protection insurer.
Build and optimize data pipelines, ETL processes, and cloud-based data platforms to turn raw data into reliable, scalable insights for businesses using tools like Azure, AWS, and Snowflake.
Build and maintain data pipelines, integrate sources, and enable analytics for clients using SQL, Python, and cloud platforms like AWS/Azure.
Build and maintain ETL/ELT pipelines on Azure using Databricks, PySpark, and Delta Lake to move and transform data for analytics and reporting.
Build and optimize cloud-based data pipelines, warehouses, and streaming APIs for diverse clients, using Python, Spark, and cloud platforms like AWS/Azure/GCP.
Build and maintain Azure-based data pipelines and warehouses for clients, using SQL, Python, and Databricks to turn raw data into scalable analytics solutions.
Design, build, and maintain scalable data pipelines and warehouses using Azure Synapse, Databricks, and Power BI to deliver insights for customers.
Build and optimize data pipelines and warehouses for clients using Azure Data Factory, Databricks, Python, and CI/CD to enable data-driven decisions in sectors like energy, healthcare, and logistics.
Build and migrate data pipelines to Microsoft Fabric, enabling analytics and AI agents while collaborating with data scientists and GIS specialists.
Build and maintain scalable data pipelines and analytics solutions for clients in industries like healthcare, logistics, and fintech using Python, SQL, Azure, Spark, and Kafka.
Design and build big-data platforms and self-service BI solutions using Azure services, SQL, Python, and Databricks to advise and implement analytics systems for clients.
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