• Performed data collection, cleansing, and validation using Python and SQL for healthcare insurance datasets to ensure high-quality data for analysis, driving informed decision-making and improving patient outcomes.• Designed and maintained ETL processes and data pipelines for seamless integration of data from multiple sources, ensuring efficient extraction of raw data, transformation for quality and consistency, and loading into centralized repositories, thus enabling real-time access to critical business information.• Created interactive and insightful dashboards in Power BI, translating raw data into actionable insights to support strategic initiatives and stakeholder reporting.• Conducted data migration and integration projects, utilizing MySQL to consolidate data from various sources, streamlining access to critical business information.• Implemented Jenkins pipelines to automate ETL processes, significantly reducing manual intervention and improving data refresh rates by 30%.• Conducted advanced statistical analyses and predictive modeling to uncover trends, patterns, and correlations, helping the business identify growth opportunities and mitigate risks.• Implemented data governance practices within Oracle, ensuring compliance with data quality standards and enhancing data security measures to protect sensitive information.• Utilized Snowflake for cloud data warehousing solutions, enabling scalable and efficient data storage, processing, and analysis across the organization.• Utilized cloud platforms like AWS to store, process, and analyze large datasets, ensuring scalable, secure, and efficient data handling across the organization.• Provided data-driven recommendations and reports to leadership, using data storytelling techniques to simplify complex findings and guide decision-making processes.

• Consolidated extensive customer data from transactional databases, CRM platforms, and customer feedback systems into a unified repository, managing over 1 million records.• Designed and executed complex SQL queries to extract, merge, and integrate data into Oracle databases, ensuring data completeness and accuracy across all datasets. • Engineered Python scripts for ETL processes, automating data extraction, transformation, and loading tasks, reducing manual effort by 15 hours per week and minimizing errors.• Leveraged NumPy for advanced numerical computations and Pandas for sophisticated data manipulation tasks, including dataset merging, data filtering, and the creation of new calculated fields. • Developed insightful visual representations using Power BI, effectively translating complex data patterns, correlations, and trends into easily digestible formats for stakeholder comprehension.• Leveraged AWS services including EC2 for scalable computing resources, S3 for secure and durable data storage, Lambda for serverless data processing tasks, RDS for relational database management, and RedShift for data warehousing and complex query execution.• Created dynamic, interactive dashboards in Power BI to visualize churn predictions, customer segmentation, and key performance indicators, providing stakeholders with real-time insights.• Developed detailed Excel reports featuring pivot tables, charts, and summaries to communicate analytical findings and recommendations effectively. • Managed project lifecycles using Waterfall methodology from requirements gathering through deployment, while utilizing Git for version control and presenting actionable business recommendations to clients and stakeholders based on complex data findings.

• Leveraged Python and Pandas to conduct comprehensive data mining and cleansing operations, significantly improving data accuracy for critical business analyses across multiple departments. • Designed and executed complex SQL queries in MySQL databases, extracting and transforming millions of records monthly to generate actionable insights for strategic decision-making. • Developed and maintained 15+ interactive dashboards using Power BI, visualizing key performance indicators (KPIs) and trends, which increased data-driven decision-making among senior management.• Collaborated with cross-functional teams in an Agile environment, participating in sprint planning and daily stand-ups to align analytical goals with evolving business needs and deliver timely solutions. • Implemented version control best practices using GitHub, managing a large repository of over 50+ analytical scripts and ensuring seamless collaboration among the data team.• Conducted advanced statistical analyses and predictive modeling techniques, uncovering hidden patterns and correlations that resulted in notable reductions in customer churn and increases in cross-selling opportunities. • Optimized data collection processes by automating report generation using Python and MS Excel macros, substantially reducing manual data entry and improving the overall efficiency of the analytics workflow.