12 years of IT experience spanning Data Engineering, Data Analysis, and Machine Learning Engineering. Expertise in building data pipelines and ETL processes with tools such as Python, Groovy (Java), SQL, AWS, GCP, Kafka, and Spark. Developed batch ETL pipelines to extract data from sources like MySQL, Mixpanel, REST APIs, and text files into Snowflake. Skilled in distributed data processing using Databricks for data transformation, validation, and cleaning, ensuring high data quality and consistency. Experience working with Spark (AWS EMR) to process data from S3 and load it into Snowflake. Worked closely with analytics and data science teams to support model deployment using Docker, Python, Flask, and AWS Beanstalk. Contributed to end-to-end CI/CD pipelines with tools like CodeBuild, CodeDeploy, Git, and CodePipeline. Developed and managed API gateways and web services for seamless data integration. Strong foundation in Object-Oriented Programming (OOP), writing extensible, reusable, and maintainable code. Hands-on experience with IDEs and development tools, including Eclipse, PyCharm, PyScripter, Notepad++, and Sublime Text. Proficient with Python libraries such as NumPy, Matplotlib, Beautiful Soup, and Pickle for data manipulation and visualization. Expertise in writing efficient Python code and resolving performance bottlenecks. Implemented optimized data processing pipelines to meet performance SLAs and reduce latency. Demonstrated ability to lead teams and work independently to deliver complex projects. Strong client interaction and presentation skills, effectively bridging technical and business communication gaps. Proven success in delivering solutions on time and driving collaborative teamwork. Experience working in cloud-native environments (AWS and GCP) and utilizing Kafka for real-time data streaming. Skilled in data modelling, governance, and ensuring data integrity across distributed systems. Adaptive to agile development methodologies, ensuring smooth project delivery and iteration.