• Analyze large datasets to extract insights supporting business decisions.
• Build and maintain Tableau and Excel dashboards for real-time metrics.
• Develop automated SQL and Python-based pipelines reducing manual reporting by 80%.
• Conduct EDA to detect anomalies and trends.
• Collaborate cross-functionally to define analytical requirements and deliver actionable insights.
• Implemented predictive churn models achieving 18% churn reduction.

• Designed and implemented 100+ KPIs and 30+ unified tables using Power BI and SQL for executive decision-making.
• Built centralized data lake using Snowflake and Azure Data Factory, integrating 10+ source systems.
• Created 30+ ETL pipelines processing 2TB+ daily data from ERP, CRM, and billing systems.
• Developed real-time dashboards reducing reporting latency from 48 hours to 2 hours.
• Integrated predictive analytics for churn and network outage forecasting.
• Ensured GDPR and HIPAA compliance securing sensitive data.

• Built Tableau dashboards for real-time production and packaging metrics.
• Designed KPIs improving transparency and efficiency.
• Automated reporting workflows reducing manual effort by 60%.
• Implemented predictive analytics for machine breakdowns lowering stoppages by 20%.
• Developed inventory dashboards optimizing costs by 12%.
• Improved OEE by 10%, saving $1.2M annually.

Data Warehouse Implementation & Analysis (GCP, DAGs, Cloud SQL, ETL)

Designed and implemented a robust data warehouse leveraging Google Cloud Platform. Using Google Cloud Composer, I architected three scalable environments and established a secure Virtual Private Cloud for Cloud SQL. Developed and orchestrated ETL pipelines using DAGs, ensuring smooth ingestion, transformation, and storage of large datasets. The project improved workflow efficiency, automated data processing, and provided secure, scalable analytics capabilities for cross-functional teams.

Financial Trends Dashboard in Food Sector (Snowflake, Power BI, ETL)

Developed an interactive financial analytics dashboard to monitor revenue trends, profit margins, and market performance in the food sector. Extracted large datasets from multiple sources using Snowflake and performed ETL processes for clean, consolidated reporting. Designed dynamic KPIs, time-series analyses, and visualizations in Power BI to identify growth opportunities and optimize strategic business decisions. This project resulted in a 20% improvement in strategic business insights for the client.

Sales and Revenue Analysis (Power BI, SQL, Data Visualization)

Built interactive Power BI dashboards to analyze regional sales performance and customer segmentation. Leveraged SQL for data extraction, cleaning, and transformation. Implemented KPIs, drill-down capabilities, and trend analyses to monitor revenue, profit margins, and sales efficiency. The solution helped business leaders quickly identify underperforming regions, optimize sales strategies, and make data-driven decisions, improving operational efficiency.

Customer Retention & Churn Analysis Platform (Python, SQL, Tableau, Azure)

Led the development of a predictive analytics platform to identify high-risk customers and reduce churn. Processed 5M+ customer records from CRM and transactional systems, applied exploratory data analysis, and built predictive models to assess churn probability. Developed automated ETL pipelines and Tableau dashboards to visualize customer segments and retention metrics. Collaborated with marketing and customer success teams to implement retention campaigns, achieving an 18% reduction in churn and saving ~$400K in recurring revenue.