Surendranatha Reddy C.

Linkedin: [login to view URL] I am a Senior Big Data Developer/ Data Engineer, specialized in designing and building scalable data pipelines to collect, parse, clean and transform data from multiple source systems and generate high-quality data sets for advanced analytics, dashboards, alerts, and visualizations. I have 6.5 in Data Engineering and Big Data technologies with on-prem and azure cloud. I love to connect dots and passionate about learning anything that deals with Data. • Experience in Data feasibility and Data Quality analysis, Business Requirements gathering, prioritizing the features for development, user acceptance testing. • Specialized in building robust and scalable data pipelines to collect, parse, clean and transform data from multiple source systems and generate high-quality data sets for advanced analytics, dashboards, alerts, and visualizations. • Good Experience in building Data Pipelines to ingest and transform different types of Semi-Structured Data (CSV, JSON, XML and Production Log Files) and Structured Data (Oracle, MySQL) using different Big Data Technologies. • Experience in migration of existing on-premise systems/applications to Azure cloud • Experience in leading end to end data efforts for a digital project. Experience in mentoring juniors and vendor team developers. Skillset: • Data Processing and Storage Technologies: Apache Spark, Python, SQL, Databricks, Azure Data Factory, ADLS, Cloudera, Hadoop, Hive, Impala, Pentaho DI • Programming Languages: Python, Scala, Unix Shell Scripting • Databases: MySQL, Oracle, SQL Server • Tools: Git, JIRA, Postman, Control-M, Crontab, Tableau • Project Domains: Telco, Banking, Mining, Manufacturing, Shipping and logistics Certifications : • Cloudera Spark and Hadoop Developer (CCA175) - December 2018 • Azure Cloud Fundamentals (AZ-400) - October 2020 I believe that we can achieve more on a team — that the whole is greater than the sum of its parts. I rely on others' candid feedback for continuous improvement. StackOverFlow : [login to view URL]