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Freelancer Overview

With over four years of experience in cloud-based data engineering, I have developed and managed large-scale data processing workflows using tools like Azure Databricks, Azure Data Factory, Microsoft Fabric, and SQL Server. My expertise includes building robust data pipelines, orchestrating data movement and transformation across multiple storage layers, and implementing metadata-driven frameworks to ensure high-quality, reliable, and scalable data solutions. I am skilled in Python, SQL, and PySpark, and have hands-on experience with data ingestion, ETL automation, and integrating data from diverse sources including APIs, SQL databases, and cloud storage. I have contributed to projects in domains such as healthcare and insurance, focusing on enabling analytics and supporting data-driven decision-making. My work emphasizes data quality through unit testing, monitoring, and error handling, all of which are critical for AI training data and annotation workflows. I am committed to continuous learning and collaboration, and I am passionate about leveraging my technical and problem-solving skills to support high-quality data labeling and AI training data initiatives.

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