Venkata N.
About Venkata N.
Venkata N. is a Software Engineering Lead at Fannie Mae in Plano, Texas, with extensive experience in data engineering and cloud computing.
Current Role at Fannie Mae
Venkata N. currently serves as a Software Engineering Lead at Fannie Mae, located in Plano, Texas, United States. In this role, he leads software engineering teams, ensuring project goals and deadlines are successfully met. His extensive hands-on experience with various data engineering tools and technologies, as well as his specialization in providing data engineering solutions, positions him effectively to meet both customer and business requirements.
Previous Experience at Cognizant
From 2014 to 2021, Venkata N. worked at Cognizant as an Architect/Manager in Irving, Texas, United States. Over his 7-year tenure, he developed his expertise in managing software engineering teams and provided complex data engineering solutions. His role at Cognizant allowed him to hone his skills in leading projects and ensuring the successful delivery of software solutions.
Academic Background
Venkata N. holds a Bachelor of Engineering (BE) degree in Computer Engineering from Sona College of Technology, which he completed between 1999 and 2003. He further advanced his qualifications by enrolling in a Post Graduate Program in Cloud Computing at The University of Texas at Austin, which he completed from 2021 to 2022. This academic background has equipped him with a strong foundation in both traditional and modern computing technologies.
Expertise in Cloud Computing
Venkata N. has expertise in both AWS and Azure cloud platforms. His skill set includes working with AWS Glue, S3, DynamoDB, and Azure Data Lake among other tools. His knowledge and experience in cloud computing environments make him versatile in handling projects across different platforms. His capabilities in cloud computing have been crucial in driving the success of the engineering teams he leads.
Technical Proficiencies
Venkata N. possesses an extensive range of technical proficiencies across various data engineering tools and technologies. These include AWS Glue, S3, DynamoDB, lambda, Pyspark, Azure Data Lake, Cloudera CDH, Hadoop, Hive, Impala, Spark, Flume, Sqoop, Kafka, Oracle, Teradata, IBM Infosphere Datastage, Netezza, DB2, Shell script, awk script, and Perl script. His hands-on experience with these tools enables him to design and implement complex data solutions effectively.