abhishekmanyala

Developed data cleaning routines using Python and SQL, collaborating with data scientists to automate the cleaning process for large datasets. This improved data analysis efficiency by 35% and implemented data validation framework that boosted data accuracy by 30%. Created interactive visualizations in Tableau to track key performance indicators (KPIs) and identify areas for improvement, leading to a 20% reduction in operational costs. Integrated Apache Airflow with AWS to monitor multi-stage ML workflows, with tasks running on Amazon SageMaker,and contributed to CI/CD solutions using Git and Jenkins for setting up and configuring the big data architecture on the AWS cloud. Automated data cleansing and transformation tasks by creating and maintaining complex PostgreSQL stored procedures, resulting in saving 2 hours per week for data analysis. Collaborated with marketing to design and execute A/B tests, measuring the impact of marketing campaigns on ROI. Utilized AWS services such as EC2, S3, Lambda, and Redshift leading to a 20% enhancement in data processing efficiency, cost-effectiveness, process automation, accelerated analytics, and data-centric decision-making. Led the end-to-end development of interactive Power BI reports, employing advanced DAX and Power Query modeling techniques to uncover deep data insights and drive informed decision-making. Collaborated with 10+ cross-functional teams to develop and maintain comprehensive data standards and naming conventions, resulting in a 20% improvement in data consistency and a 15% reduction in data quality issues. Crafted ad-hoc SQL queries using joins, database connections, and transformation rules to fetch and transform data from legacy MySQL and SQL Server systems, improving data retrieval speed by 20% and automating repetitive tasks.