Bengaluru, Karnataka, India
I am a Senior Data Engineer at PwC, specializing in designing, building, and optimizing large-scale data ecosystems that power business-critical insights. With 6+ years of hands-on experience in Big Data Engineering—spanning Azure, Hadoop, Spark, Databricks, Kafka, and Python—I bring strong technical expertise combined with deep domain knowledge in banking and financial services. Before joining PwC, I worked at Tata Consultancy Services (TCS) from 2020 to 2025, where I engineered robust data pipelines and modernized data platforms for major clients, including Westpac Banking Corporation and a national bank in Australia. My work has consistently focused on reliability, performance tuning, automation, and scalable architectural design. I hold a Master of Computer Applications (MCA) degree and have multiple certifications in Python for Data Science and Google Data Analytics from IBM and Coursera. I enjoy solving complex data problems, optimizing ETL workflows, and enabling organizations to unlock the full potential of their data. I am a fast learner, a strong team collaborator, and someone who thrives in transforming raw data into meaningful, actionable intelligence. At PwC, my goal is to continue driving innovation, implementing cloud-native architectures, and delivering measurable value to clients through data-driven solutions. If you’re passionate about data engineering, cloud transformation, or want to exchange ideas—let’s connect.
Developed and Integrated New Data Pipeline: Designed and implemented a new data pipeline to meet updated business requirements, ensuring seamless integration with existing data flows. Enhanced Data Processing Efficiency: Utilized Python, SQL, and Spark to develop scalable data processing solutions, reducing processing time by 30%. Collaborative Project Management: Worked closely with cross-functional teams to gather requirements, define project scope, and ensure timely delivery of the new pipeline. Quality Assurance and Reliability: Conducted rigorous testing and validation to ensure data accuracy and consistency, leading to more reliable business insights. Ongoing Maintenance and Optimization : Monitored and maintained the new pipeline, troubleshooting issues promptly and implementing continuous improvements for optimal performance.
- Gathered Data from different sources like SQL Developer, Teradata and Informatica Mapping and maintain IFS/Confluence Pages. - Ingestion and build of the large data files coming from different warehouse systems into Bigdata platform based on Microsoft Azure . - UTF-8 encoding format check on CSV files and push them to remote repository of Bitbucket from our local one via Git-bash/Pycharm. - Create and deploy the release pipeline/CI-CD in Azure DevOps. - Created Control-M job for Automation. - Performed Data Cleaning and Transformations using RDD and Data Frame and to various formats like Tables, JSON, and ORC. - Knowledge on latest languages like Spark,Python. - Design and development of the Customer Requirement along with the integrated testing and deployment of the code to production. - Creating the documents for day to day issues and updating same on Confluence. - Perform Data Validation after doing Data Ingestion into Test and Prod Environment. - POC on new process with different test cases.