As a Data Engineer with over 4+ years of experience, I leverage big data, cloud-based ETL, and real-time reporting to drive decision-making and improve business outcomes. With expertise in SQL, Python, PySpark, AWS (Lambda, RDS, SQS, EC2, ECR, EMR, SNS, Event Bridge, Cloudwatch), Apache Airflow, Snowflake, and Power BI, I have successfully built scalable data pipelines and automated workflows to enhance data accessibility and operational efficiency. I have collaborated with cross-functional teams and key stakeholders throughout my career to design data solutions that optimize performance and reduce costs. I have experience developing real-time dashboards, data models, and monitoring solutions that improve system reliability and business insights. My work has helped reduce ETL latency by 20%, optimize processing costs by 25%, and enhance report generation speed by 80%. Additionally, I hold a Master’s degree in Data Science from VIT University and have a strong foundation in machine learning, deep learning (TensorFlow, PyTorch), and NLP. I am passionate about solving complex data challenges, optimizing data workflows, and staying updated with the latest trends in data engineering and analytics. If you're looking for a data engineer who can help build and optimize data-driven solutions, feel free to connect with me!