 Facilitated the progression of data analysis tasks through distinct phases within a structured Waterfall framework, ensuring meticulous planning and execution.  Created Python scripts to automate data cleaning processes, reducing manual effort by 30%.  Employed Python libraries (NumPy, Pandas, Matplotlib) to engineer intricate data manipulation strategies, improving data processing efficiency by 30% and providing critical insights that enhanced decision-making accuracy by 25%. Produced insightful reports using Power BI, enabling data-driven decision-making through comprehensive data summaries.  Improved Excel models for financial analysis, reducing errors by 20% and saving 2 hours per week.  Optimized SQL Server queries, resulting in a 15% reduction in database response times.  Implemented data transformation logic using Python, SQL, or ETL tools such as Informatica or Talend

 Collaborated within Agile teams, fostering iterative analysis and adapting to evolving project needs for agile-driven data solutions. Experience in Business Intelligence and Data Warehousing Concepts with emphasis on ETL and System Development Life Cycle (SDLC).  Created visual representations, graphs, and statistical plots using Matplotlib, Seaborn, ggplot2, Scipy, and Plotly to conveycomplex data insights effectively, leading to a 35% increase in data comprehension among stakeholders. Developed VBA scripts to automate the merging and splitting procedures, resulting in a 30% reduction in manual effort and a 25% decrease in errors.  Completed data migration projects, reducing data transfer time by 20% and ensuring data security during migration to AWS cloud platforms, resulting in a seamless transition and zero data loss.  Settled and automated financial reports and dashboards using tools such as Tableau and Power BI, providing actionable insights to stakeholders and reducing report generation time by 40%. Conduct comprehensive financial analyses including trend analysis, variance analysis, and forecasting to identify key business drivers and opportunities for improvement.  Developed dashboards in Tableau and presented data to track KPIs and product performance using data from various sources such as MS Excel, AWS S3, AWS RDS, AWS Redshift, JSON and XML.  Wrote scripts to store data into Hadoop from various sources including AWS S3, AWS RDS and Web API and NoSQL Database MongoDB.  Managed NoSQL databases and big data tools including Hive and Spark.