Data Engineer Digital Customer

Venkata Nageswara Manish Wunnava

http://www.linkedin.com/in/manishwvn/ https://github.com/manishwvn ************@*****.*** +1-213-***-**** Sunnyvale, CA Professional Experience

Data Engineer, CVS Health April 2023 – Present

● Enhanced digital customer interactions as part of Retail Offer Channel Management (ROCM) team by optimizing and delivering multi-channel communications

(SMS, Voice, Email, Push notifications) to customers.

● Notification Suppression Counts Reduction - Improved Oracle Stored Procedures to identify reasons for notification suppression, over 50,000 daily SMS and voice call operations. Boosting outreach and increased customer engagement by 30%.

● Channel Expansion to Non-SMS Pharmacy programs - Led the expansion of email and push notification systems in 9,000+ pharmacies, while developing optimized Oracle PL/SQL procedures to automate workflows, ensuring efficient production deployment through robust testing.

● Upgraded end-to-end data pipelines using Data Definition and Data Manipulation queries, Stored procedures, and UNIX shell scripting to identify opportunities in 'Healthcare Gaps', collaborated with multiple product teams, and provided extended on-call support.

● Identified and delivered priority technical debt using SQL scripting for the resolution of PUSH offers in data generation frameworks for downstream systems.

● Configured 200+ No Surprises Act (NSA) templates to comply with Federal regulation through BMC Control-M Automation jobs to provide 5 million daily Real-Time notifications to customers.

Software Development Engineer, Amazon.com May 2022 – Aug 2022

● Designed and developed features for a data lineage application, "Pathfinder", optimized search retrieval from hours to under 5 seconds, boosting business teams' productivity and saving developers' efforts.

● Engineered and tested application components using React, TypeScript, and AWS services - DynamoDB, Lambda, and S3, increasing efficiency by 130%.

● Implemented APIs to optimize search queries in DynamoDB, improving request execution and enhancing React front-end integration.

● Proactively worked as the primary point of contact between Business teams and Data Engineers, ensuring data correctness through User Acceptance Testing (UAT). Database Engineer Intern, Bharat Heavy Electricals Ltd. Jun 2020 – Nov 2020

● Migrated historical and current purchase data to the SAP S/4HANA ERP system, improving data accessibility and contributing to operational efficiency by 50%.

● Designed data models using SQL and Python, ensuring seamless data integration and reducing development overhead by 40%.

● Performed data analysis and visualization to support the data migration process, providing insights that enhanced the transition to the new system. Skills

● Programming Languages: Python, SQL, PL/SQL, Java, Bash/Shell Scripting.

● Tools & Frameworks: Apache – Spark, Hadoop, Kafka, Airflow, Docker, Linux, Tableau, PowerBI, PyTorch, Git, Pandas, Snowflake, Databricks.

● Databases & Cloud: Oracle, MySQL, PostgreSQL, MongoDB, DynamoDB, SAP S/4HANA, Amazon Web Services (AWS), Google Cloud Platform (GCP), Azure.

● Expertise: Big Data (ETL Pipelining and Modelling), Data Warehousing, Database design, Query Optimization, Data Analysis, Visualization. Technical Projects

Data Warehousing and Analysis using YouTube Trending Videos Data:

● Designed and developed a comprehensive pipeline to build a data warehouse in AWS Redshift using YouTube Trending Videos Dataset, ranging up to 30000 records.

● Created ETL jobs using Python on AWS Lambda, reducing time for data preprocessing by 40% to build efficient data crawlers on Glue and designed data schemas.

● Utilized AWS QuickSight to analyze and visualize the processed data from the data warehouse to gain insights such as view categories, regions, number of likes, etc. Real-Time Stock Market Data Processing Pipeline

● Designed and developed an ETL pipeline for real-time stock market data averaging over 100,000 records using Apache Kafka, AWS, and Python, reducing data processing time by 50%.

● Improved system stability utilizing AWS EC2 and Zookeeper, intelligently fixed issues to reduce server downtime by 90%.

● Employed strategies such as staging data in S3, creating data catalog using Glue crawler and Athena for data modeling and analysis using SQL, increasing efficiency by 25%.

Recommendation systems using Yelp California data

● Developed recommendation systems using the Yelp dataset of over 400MB, employing user-based, item-based, and hybrid approaches of Min-Hash LSH algorithms with Python and Apache Spark RDD for big-data processing, analysis, and visualization.

● Achieved recommendation system accuracy of 98% using the hybrid approaches for finding similar business pairs using Jaccard Similarity. Education

University of Southern California, Los Angeles, California

● Master of Science, Computer Science

● Coursework: Algorithms, Artificial Intelligence, Database Systems, Machine Learning for Data Science, Information Retrieval, Web Technologies. GITAM Deemed to be University, Visakhapatnam, India

● Bachelor of Technology, Computer Science and Engineering

● Coursework: Data Structures, Object-Oriented Programming, Data Mining, Operating Systems, Computer Networks. Publications

Delineation of Autonomous Driving Cars in Simulator Ambience Using Deep Learning - International Journal of Advanced Science and Technology, 29(3), 12057 - 12065. (Link)

● Implemented deep learning models for autonomous car agents in simulated environments using OpenCV, Pandas, and advanced image processing techniques, while enhancing dataset size and quality by 300% and achieving around 95% validation accuracy.

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