Kumar T

About Kumar T

With a solid background in leading medium to large IT projects, my role as Manager IT at FedEx Services focuses on digital transformation, e-commerce, and legacy modernization. Our team endeavors to streamline architecture delivery and enhance infrastructure management. We pride ourselves on implementing software development tools and object-oriented programming to bolster web performance, contributing to the organization\'s robust digital presence. My expertise in vendor management and production support has been instrumental in building teams that flourish in high-stakes environments. By fostering a culture of empathy and motivation, we\'ve successfully engineered processes that expand market share and surpass revenue objectives. At FedEx Services, we harness the power of cloud infrastructure to pioneer innovative solutions that resonate with the evolving demands of the digital era.

Experience

1. Data Engineer

   Cigna Healthcare

   Dec 2023 — Present · Memphis, TN, US

   Designed, developed, and maintained data pipelines and ETL processes using Azure Data Factory, Azure SQL Database, Azure Data Lake Storage, and Azure Blob Storage, resulting in improved data accessibility and efficiency.• Implemented data transformation and manipulation using Python and SQL, ensuring data consistency and accuracy throughout the pipeline.• Utilized Power BI for data visualization and reporting, providing actionable insights to stakeholders and decision-makers.• Collaborated with cross-functional teams to define data requirements and ensure alignment with business objectives.• Conducted data quality assessments and testing to validate data integrity and reliability, ensuring compliance with industry standards and regulations.• Worked on Big data, AWS cloud services including EC2, S3, EMR, and DynamoDB.• Worked on end-to-end machine learning workflow, written python code for collecting data from AWS snowflake, data preprocessing, feature extraction, modelling, evaluating the model, and deployment.• Integrated machine learning algorithms into data pipelines to automate predictive analytics and optimize data processing workflows.