Neeraj Nadajoshi

Project 1: Analytical Workbench / M360 – Commonwealth Bank of Australia

• Developed end-to-end data integration solutions using Apache Spark, SQL, and Shell scripting, ensuring data accuracy and compliance.
• Optimized ETL pipelines for HDFS ingestion, reducing data latency by 25% and improving system reliability.
• Increased operational efficiency by automating workflows with Unix Shell scripting, cutting manual effort by 40%.
• Improved SQL query performance by 30% using Hive with optimized partitioning techniques.
• Automated ETL pipelines with Autosys, achieving a 95% job success rate and reducing errors by 20%.
• Designed and implemented delta ingestion strategy to handle real-time updates without reprocessing entire datasets.
• Collaborated with DevOps teams to implement CI/CD pipelines, reducing deployment failures and improving release cycles.

Project 2: CPBB Retail Banking – Standard Chartered Bank

• Built and optimized data pipelines to migrate retail banking data to AWS Athena using Hadoop & Python.
• Improved data transformation efficiency by 25% using Pandas & NumPy for large datasets.
• Reduced query response times by 20% using AWS Athena and Hadoop for efficient data lake integration.
• Automated data cleansing and validation processes, ensuring 99% data accuracy and reducing manual corrections.
• Developed optimized partitioning strategies in AWS Athena, cutting unnecessary query costs by 30%.
• Partnered with business analysts to align pipeline outputs with BI requirements.
• Created real-time monitoring dashboards to track ETL job execution and failures, reducing resolution time by 50%.