Saisri Vegesna

Background

About Saisri Vegesna

Big Data Developer/ Data Engineer with around 3 years of experience in the design and development of analytics/Bigdata applications using leading industry tools, working with fortune firms. Hands on experience in installing configuring and using Hadoop ecosystem components like Hadoop, HDFS, HBase Hive Sqoop Pig Zookeeper and Flume. An accomplished Hadoop/Spark developer experienced in ingestion, storage, querying, processing and analysis of big data. Strong skills in python programming language and PySpark Experienced in WAMP (Windows, Apache, MYSQL, Python) and LAMP (Linux, Apache, MySQL, Python) Architecture. Understanding of Python Best Practices (PEP-8). Experience in complete Software Development Life Cycle (SDLC) in Agile methodologies. Knowledge in Tableau server commands to migrate workbooks and Tableau server backup, Debugging and monitoring. Good Experience and strong skills in a high - level Python Web framework. Experience object-oriented programming (OOP) concepts using Python, Django, and Linux. Optimization of Hive queries using best practices and right parameters and using technologies like Hadoop, YARN, Python, PySpark. Developed spark applications in python(PySpark) on distributed environment to load huge number of CSV files with different schema in to Hive ORC tables. Worked on reading and writing multiple data formats like JSON, ORC, Parquet on HDFS using PySpark. Analysed the SQL scripts and designed it by using PySpark SQL for faster performance. Expert at PySpark tunings for performance improvements. Responsible for creating the design documents, establish specific solutions, creating the Test Cases. Responsible for closing the defects identified by QA team and responsible for managing the Release process for the modules. Good understanding of HDFS Designs and HDFS high availability (HA). Good working experience in importing data from various sources like RDMS, Teradata, Mainframes, Oracle, Netezza to HDFS and performed transformations and aggregations on it using Hive, Pig and Spark. Expertise in using optimization techniques on Hive tables such as Partitioning, Bucketing, and Vectorization. Extensive Knowledge to convert Hive/SQL queries into RDD transformations in Apache Spark. Worked on CLI and GUI based Hive Interaction tools like Hue, Impala, and Tez for querying the data. Experience in writing Complex HQL queries for filtering the data loaded in Hive tables. Solid understanding of Workday calculated fields.