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Design and maintain scalable data pipelines using AWS, Databricks, and Python to process and integrate healthcare data for analytics and reporting.
Design and maintain cloud-based data pipelines and the enterprise Master Data Repository in Azure, enabling reliable data flows and analytics for a high-tech electronics manufacturer.
Design and maintain data pipelines using Databricks, Python, and PySpark in Azure/AWS to build scalable ETL/ELT solutions for analytics and reporting.
Build and maintain scalable cloud data pipelines in Azure, transforming raw data into insights using PySpark, Databricks, Fabric, and Snowflake for clients in healthcare, retail, energy, and government.
Build and maintain SendCloud’s data lakehouse and pipelines on AWS, enabling AI-driven decisions and agentic workflows for global shipping logistics.
Build and maintain a scalable data platform using Azure, PySpark, Delta Lake, and Microsoft Fabric to power analytics and decision-making across the organization.
Build and maintain Azure Databricks and Microsoft Fabric data pipelines, ETL/ELT processes, and Lakehouse architectures to deliver reliable data for analytics and reporting.
Build and improve a data foundation for a large retail client, implementing data products, pipelines, and governance to enable a data mesh architecture using GCP, SQL, Python, and dbt.
Builds scalable cloud data pipelines and AI-ready platforms using Python, PySpark, DBT, and SQL, transforming raw data into insights for customers and internal products.
Builds and migrates Python/PySpark data pipelines on Databricks for corporate credit-risk models, converting SAS code and ensuring data quality and performance.
Design and build scalable data pipelines and cloud architectures (Azure, Databricks, Snowflake) to power analytics and AI solutions for clients.
Lead role designing and building scalable data pipelines, ETL processes, and cloud data infrastructure (e.g., Databricks, Snowflake) to power analytics and AI projects for clients in retail, finance, and healthcare.
Builds scalable data pipelines and ensures data quality using Python and PySpark for a fintech company in Amsterdam.
Design and build ETL pipelines in Python to merge banking data from Oracle, SQL Server, APIs and flat files into a target data warehouse.
Build and maintain data pipelines in Python to ensure high-quality B2B lead data for a fast-growing marketing platform.
Build and maintain a Python-based ETL framework that ingests, transforms, and delivers financial data using Spark, Azure Databricks, and Airflow.
Leads backend architecture on Azure and Databricks, building cloud-native pipelines with PySpark and SQL Server while guiding CI/CD and mentoring engineers.
Build internal tools, APIs, and AI-powered apps to support engineering and operations for a cleantech firm tackling water sustainability and lithium refining.
Build and maintain scalable data pipelines using PySpark, Databricks, and Airflow to integrate financial data from APIs, Oracle, and Kafka into a data warehouse/lakehouse.
Build and optimize data pipelines, warehouses, and analytics for a banking-focused data platform using SQL, Python, and cloud tools.
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