Hetal Vaghela

•Designed and built data pipelines and analytics workflows supporting healthcare reporting, inventory tracking, and operational decision-making in cloud-based environments. •Developed ETL pipelines using Python and SQL within the Hadoop ecosystem, automating data ingestion and transformation and improving processing efficiency by 40%. •Optimized Apache Spark batch pipelines processing warehouse and supply chain datasets, reducing batch processing time by 30% while maintaining data accuracy and reliability. •Implemented real-time streaming pipelines using Apache Kafka to process pharmacy inventory and order events, applying schema validation and governance checks to improve data quality by 30%. •Improved analytics performance by enabling serverless querying with Amazon Athena on S3, reducing query response times by 20%. •Contributed to the development of CI/CD pipelines and DevOps workflows for data applications, reducing deployment errors by 25% and improving release stability. •Collaborated with engineers, analysts, and product partners using Agile practices, helping accelerate development cycles by 20%. •Built interactive dashboards in Amazon QuickSight to visualize prescription trends and inventory metrics, improving operational visibility and decision-making efficiency by 25%. Tech Stack: Python, SQL, AWS (Glue, S3, Athena, QuickSight), Apache Spark, Apache Kafka, Hadoop, CI/CD, DevOps

•Developed and maintained cloud-based data pipelines using GCP Dataflow, unifying transactional and structured data sources with production-grade testing and validation. •Integrated Hadoop and Apache Spark with relational databases to support financial data warehousing and OLAP workloads, reducing data retrieval latency by 50%. •Contributed to the migration and adoption of Snowflake as a cloud data warehouse, improving scalability and reducing query execution time by 45% for analytics workloads. •Built data marts and dimensional data models using Google BigQuery, improving reporting accuracy by 35% and enabling efficient financial analytics. •Implemented MapReduce and batch processing jobs to transform large-scale datasets, improving data accuracy and supporting enterprise reporting pipelines. •Applied machine learning models using TensorFlow and Scikit-learn to forecast financial market trends, improving prediction accuracy by 20% and supporting risk analysis use cases. •Supported containerized data workflows using Docker and Kubernetes, improving scalability and operational consistency of data processing services. •Developed financial dashboards using Google Data Studio, providing near real-time insights and improving strategic decision-making efficiency by 40%. Tech Stack: GCP, Python, SQL, Hadoop, Apache Spark, Snowflake, BigQuery, TensorFlow, Scikit-learn, Docker, Kubernetes

Half Tuition Waiver & Graduate Assistantship – Awarded based on academic excellence and research contribution throughout the program. • Core Coursework: • Data Management Systems • Business Intelligence • Business Programming • Big Data Analytics • Project Management • Collaborated on data-driven research projects focusing on predictive analytics and cloud-based ETL optimization. • Actively mentored new international students as part of the International Student Organization, assisting with onboarding, visa workshops, and cultural adaptation. • Led initiatives to organize campus-wide events promoting cross-cultural exchange and community building. • Represented the university in multiple graduate research symposiums, showcasing work in big data processing and machine learning integration.

• Core Technical Coursework: • Programming Languages: Java, C, C++, Python • Web Technologies: HTML, CSS, JavaScript, C#, ASP.NET MVC • Database Management Systems (DBMS), SQL • Big Data Fundamentals and Ecosystem • Software Engineering & Object-Oriented Programming • Operating Systems, Data Structures, and Algorithms • Completed multiple hands-on academic projects in full-stack development and database design, applying industry best practices. • Participated in coding competitions and internal hackathons, achieving recognition for logical problem-solving and efficient code structure. • Served as a peer tutor for foundational programming courses, helping juniors strengthen their coding logic and debugging skills. • Organized tech workshops and seminars as part of the university’s IT Club, focusing on emerging technologies like Big Data and Web APIs.