Jitendra Gupta

About Jitendra Gupta

15 years of experience in designing, developing, and implementing complex ETL pipelines and data engineering solutions.• A proven data leader who thrives on solving ambiguous problems and delivering scalable solutions that drive business impact.• Expertise in data warehousing, ETL processes, and scalable data pipelines across various cloud and on-premises environments.• Strong proficiency in translating business requirements into robust technical solutions with a focus on performance optimization.• Excellent communicator, adept at working independently and in collaborative, fast-paced environments.• Extensive experience in project management, including CI/CD deployment, troubleshooting, and maintaining data integrity.

Experience

1. Senior Data Engineer

   Amazon

   Sep 2017 — Present · Seattle, WA, US

   Led an S-team goal to achieve 40% analytical data registration of Amazon Retail data in S3 into the Andes Data Lake to enhance governance and operational capabilities• Designed, Modeled and implemented scalable big data solutions processing trillions of records, leveraging AWS S3, Glue, Redshift, and Apache Spark to enable accurate analytical data registration reporting into the Data Lake• Led the complete redesign of Amazon\'s Offer Listing pipeline (handling 50 billion records daily), modernizing a decade-old system to enable intraday processing and unlock new customer use cases like fraud analytics, Inventory Planning etc.• Redesigned pipeline achieving 40% faster processing time and 30% storage reduction, cutting operational costs while enabling rapid business insights and enhanced scalability• Designed, modeled, and delivered \"Loom,\" a provenance based centralized lineage solution for Andes Data Lake, enabling end-to-end tracking of data flow for ~500K tables across Amazon’s enterprise data ecosystem, addressing governance, compliance, and operational needs.• Overcame complex challenges in modeling metadata using the Provenance framework by devising innovative solutions for parameterized datasets, logical-to-physical DB mappings, and scalable lineage computation, generating 1.2M files in S3 to support API-based lineage queries.• Led the development of scalable workflows to compute and store lineage data, optimizing Spark and AWS Glue processes to handle 100K+ files efficiently while reducing compute costs and ensuring data integrity.• Migrated application systems from Oracle to Amazon Redshift and Data Lake as part of Amazon\'s Oracle Shutdown initiative, ensuring seamless data transition and improved scalability and cost saving up to 60% of cost• Mentored junior engineers, fostering a culture of technical excellence through code reviews, knowledge sharing, and leadership in design discussions.

Education

• Rajiv Gandhi Institute of Technology

  BEIT, Information Technology

  2006 — 2009

Skills

• Business Process
• Business Intelligence
• Netezza
• Databases
• Microsoft Sql Server
• Sdlc
• Unix
• Data Modeling
• Agile Methodologies
• Etl
• Javascript
• Data Warehousing
• Oracle
• Requirements Analysis
• Sql
• Db2
• Shell Scripting
• Xml
• Business Analysis
• Requirements Gathering
• Pl/Sql
• Extract, Transform, Load (Etl)
• Html
• Performance Tuning
• Teradata
• Informatica
• Unix Shell Scripting