Pooja Vishwakarma

Note - career break due to Personal Reasons

• Architected IoT data flows handling 8TB datasets and 8GB daily ingestion for real-time analytics.
• Integrated REST APIs and Event Hub for near real-time manufacturing & retail analytics.
• Built Spark-based pipelines for batch/streaming data; created insights visualized in Power BI dashboards.
• Developed automation frameworks for CI/CD deployment of pipelines.
• Improved anomaly detection by analyzing IoT datasets with Spark.
• Designed and implemented large-scale data pipelines using Hadoop ecosystem (HDFS, Hive, Sqoop, Flume, Oozie) to process structured and unstructured data.

• Built end-to-end pipelines using Azure Databricks, ADF, and PySpark, ensuring seamless reporting.
• Delivered interactive sales dashboards in Power BI, improving decision-making efficiency.
• Optimized large-scale transformations using Spark for highperformance data processing.
• Built data lake architecture on HDFS, enabling centralized storage and efficient querying of petabyte-scale data.

• Spearheaded Azure & Databricks pipelines, driving significant supply chain cost savings.
• Developed scalable datasets for automation initiatives via Power BI & PowerApps.
• Contributed to DevOps-enabled pipeline deployment for reliable workflows.
• Conducted POCs and product innovation for continuous improvement.

• Built a Customer Affiliation Model, improving retention and CRM strategies.
• Led ETL processes for data extraction, transformation, and cleansing to ensure quality.
• Applied regression analysis for data validation and insights.
• Performed UAT and reporting using Cognos, enabling vendorlevel insights.