May 2022 – Dec 2024 · 2 yrs 7 mos

• Architected and implemented a Spark‑based generic data correction tool that demonstrated robust performance across diverse data sizes from MBs to 100 GBs.
• Conducted comprehensive performance testing to ensure universal applicability across data warehouse tables.
• Led the development, debugging, and management of 15+ data pipelines, processing terabytes of customer data for various products like insurance, consumer
• loans, and credit cards. Proficiently utilized PySpark, Hive, HDFS, SQL, and Pandas to drive accurate and efficient sales reporting and analytics.
• Designed and implemented a robust historical data correction solution that enhanced the accuracy of sales commission calculations; received accolades for
• resolving data integrity issues impacting over 1000 transactions weekly.
• Developed a proactive alerting and monitoring framework for 200+ daily, weekly, and monthly jobs, enhancing production support efficiency and minimizing
• downtime through real‑time email alerts and an intuitive dashboard.
• Applied Spark optimization techniques such as broadcasting, caching, memory allocation, and partitioning, resulting in a 36% performance improvement.
• Performed multiple experiments with various compression techniques such as gzip and snappy, and file formats including Avro, CSV, and Parquet. Enabled
• smooth data migration from on‑prem HDFS to GCS buckets and BigQuery. Optimized data storage and retrieval, reducing space usage by 36% and query execution
• time by 20%.
• Facilitated the migration of 4+ million Postbank customers to Deutsche Bank’s IT system as part of the ”Unity Program” consolidating both brands into a unified
• system, streamlining operations using Data Vault Modeling framework.
• Collaborated with 30+ data engineers, testers, and business leads throughout the SDLC, utilizing agile methodologies to ensure seamless project delivery. Main‑
• tained high coding standards through unit tests, thorough documentation, and regular code coverage analysis.

Jul 2021 – Apr 2022 · 9 mos

• Successfully processed and analyzed hundreds of thousands of images to determine relevant features for a Computer Vision‐based car insurance claim application.
• Conducted damage segmentation and classification based on various attributes ,such as size ,type , part, and angle, improving mAP by11%.
• Created metadata in Json format using VGG annotator for each image in the dataset and collaborated closely with the data science team on object detection and character recognition.

Nov 2020 – Jan 2021 · 2 mos · Bengaluru, Karnataka, India

Jul 2019 – Sep 2019 · 2 mos · Guwahati, Assam, India