- Established and enforced best practices for data governance and quality, driving initiatives to deliver clean, accurate data for advanced analytics, and machine learning projects, ensuring robust support for business intelligence needs.- Designed and optimized ETL and data processing pipelines using Python and SQL to streamline efficient data migration to cloud-based platforms like Snowflake and AWS, emphasizing performance, scalability, and automation.- Managed snowflake data warehouses, implementing scalable architectures, and optimized data workflows using Apache Airflow and AWS, while enhancing data reliability to support software development.- Streamlined complex data workflows by integrating CI/CD practices, boosting data quality and reliability, and improving backend infrastructure to empower machine learning model deployment, data science analytics, and automated reporting.- Led initiatives to enhance data processing capabilities, implementing rigorous unit testing and data validation to maintain data quality standards, ensuring consistent support for evolving software development.

- Designed and built CI/CD pipelines to automate and streamline the development and deployment of data visualization products on GitHub, reducing development cycle times and enhancing productivity, enabling rapid updates and ensuring version control.- Led the development of a web-based data visualization tool using Python, JavaScript, and D3, increasing user engagement by 30% and making complex data accessible and actionable for users through enhanced interactivity and design.- Engineered ETL workflows to automate data extraction from NASA servers, followed by data cleansing, transformation, and loading into databases, optimizing pipeline efficiency, conserving resources, and guaranteeing high data quality for downstream applications.- Created automated scripts to generate images from XML requests, significantly improving processing speed and accuracy while streamlining data transformation and enriching data pipelines for further analytics.- Developed robust APIs using Python’s PyDAP to facilitate seamless interaction with NASA's OPeNDAP servers and other public servers, enabling efficient data retrieval and integration for scientific research, analysis, and satellite data processing, contributing to high-impact, data-driven decision-making.

• Performed web scraping using Selenium and API keys• Performed data analysis based on key metrics from different blockchain platforms

- Gathered, arranged, and corrected research data to create representative graphs and charts highlighting results for presentation CGS conference 2021- Completed research and compiled data and assisted in focusing on Ecological Forecasting time series on remote sensor data

• Conducted data preparation, data cleaning and data visualization on different projects. Projects included COVID-19 cases, housing market, Poisonous Mushroom Classification, etc.• Applied different Machine Learning models on the assigned projects with algorithms focused on SVM, Decision Tree, Logistic Regression, and K-Means clustering.• Analyzed and presented the classification of poisonous mushrooms based on extracted mushroom features using Logistic Regression and Decision Tree.• Performed cluster analysis to identify significant grouping feature of COVID-19 cases around the world.• Computed projects analysis with MySQL, Python, Jupyter Notebook, NumPy, Graphviz, pandas, sklearn models and metrics.

- Designed and coordinated engineering tests and experiments- Tested prototypes and standard products and wrote reports to document results