About Me
As a Data Engineer currently working at Johnson & Johnson within the supply chain domain, I bring a wealth of technical expertise to the table. My proficiency spans Python, SQL, PySpark, Azure Data Factory, Databricks, and ADLS, enabling me to construct resilient data pipelines and automate processes with precision. I excel in optimizing code, ensuring that our data processing operations are not only efficient but also scalable. This role demands a keen understanding of both the technical intricacies of data management and the broader strategic goals of our supply chain operations. I thrive on the challenge of integrating disparate data sources, refining algorithms, and leveraging parallel computing to enhance performance. By automating routine tasks and streamlining data workflows, I contribute directly to the operational agility and analytical capabilities that drive decision making at Johnson & Johnson.
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