SRINIVASULU PONUGUPATI

Nike has a huge IT applications and one of the significant one is PDI (product data and integration), which process the product information and integrate to different outbound systems.

• Developed scalable Data Pipelines using Databricks &Snowflake capable of handling vast amounts of structured and unstructured data, improving overall system performance.
• Evaluated new technologies and industry trends to identify opportunities for enhancing current systems or developing innovative solutions.
• Built ETL pipelines using Databricks (Spark) from Kakfa stream sources with data transformation to cleanse and curate data to prep data for analytics.
• Evaluated a variety of documentation, modeling diagrams, created process flows, data flow, &
  entity relationship models in order to teach & present on a higher-level to a less technical
  audience.
• Enhanced data quality and reliability for real-time analytics by designing and deploying robust data pipelines.
• Mentored junior engineers on best practices in data engineering, fostering a culture of continuous learning and improvement within the team.
• Identified areas for improvement within existing ETL frameworks to maximize efficiency without sacrificing accuracy or integrity of results produced during transformations applied on ingested datasets.
• Fully automated pipeline using containerized infrastructure as code, CICD processes, & an event-driven system.
• Developed scalable infrastructure capable of handling vast amounts of structured and unstructured data, improving overall system performance.

Carters got merged with OSHKOSH BGOSH; This is a migration project between the Carters and Oshkosh databases for internal planning and resource allocations.

• Delivered exceptional results under tight deadlines, consistently prioritizing tasks effectively to meet project timelines without compromising quality or accuracy.
• Collaborated on ETL (Extract, Transform, Load) tasks, maintaining data integrity and verifying pipeline stability.
• Analyzed large datasets to identify trends and patterns in customer behaviors.
• Compiled, cleaned and manipulated data for proper handling.
• Worked in the data analytics space providing data management & transformations to prep data
  for analytic needs & then created dashboards & data visualizations to tell a story with the data.
• Created E2E Data Pipelines using Oracle Pl/Sql Procedures and other Oracle Objetcs (Tables, Mviews, Views, Triggers).
• Reengineered existing ETL workflows to improve performance by identifying bottlenecks and optimizing code accordingly.