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Performed comprehensive data profiling on cloud-based operational datasets using SQL and Python (Pandas, Seaborn), identifying inconsistencies and outliers to improve reliability of product analytics pipelines. • Designed and developed Tableau dashboards to visualize feature adoption, usage patterns, and customer engagement metrics for key cloud-native products. • Improved Snowflake SQL query performance for scheduled reports by tuning joins and filters, reducing dashboard refresh time by 40% and optimizing cloud compute cost. • Contributed to the validation and monitoring of ETL pipelines hosted on AWS, enabling accurate data feeds into internal ML models for churn prediction and usage forecasting. • Maintained end-to-end documentation of data lineage, metric definitions, and architecture flow using Confluence, Lucid chart, and Jira, driving alignment across data, product, and engineering teams.

Built real-time dashboards using Tableau and Power BI to track client transaction trends, reducing decision time by 15% and supporting data-driven strategies. • Used Python (Pandas, NumPy) and SQL for large-scale data wrangling and automation, cutting daily reporting time by 30% and enhancing data quality. • Conducted exploratory data analysis (EDA) and contributed to fraud detection models using R and Python, helping identify high-risk patterns and reduce fraud by 15%. • Collaborated with the data engineering team to support AWS Redshift integration, enabling faster query performance and more reliable cloud-based reporting. • Delivered insights to cross-functional teams and business clients, improving customer engagement by 12% and shaping marketing strategies with predictive analytics.

Delivered actionable business insights by analysing large datasets using SQL, Power BI, and Python, enabling leadership to monitor KPIs and optimize operational performance. • Supported the development of predictive analytics models using Python and scikit-learn to improve customer retention and product demand forecasting across regions. • Collaborated with the data engineering team to automate ETL workflows using Apache Airflow, enhancing data pipeline reliability and reducing manual processing time. • Improved query performance for PostgreSQL and MySQL databases by contributing to index optimization and analyzing slow-running queries for key business reports. • Contributed to the design and deployment of interactive dashboards for cross-functional teams, streamlining weekly reporting and enabling data-driven decision-making.