Ashish Ranjan
About Ashish Ranjan
Ashish Ranjan is a Data Management Team Lead at ArisGlobal in Bengaluru, Karnataka, India, with eight years of experience in data warehousing and management. He has engineered a data warehouse using both Inmon and Kimball methodologies and possesses expertise in various data modeling techniques and modern data technologies.
Work at ArisGlobal
Ashish Ranjan has been serving as the Data Management Team Lead at ArisGlobal since 2016. In this role, he is responsible for overseeing the design and development of data management systems. His leadership involves implementing engineering best practices to improve the quality and reliability of team outputs. He also addresses customer issues and escalations related to product implementation, showcasing his problem-solving capabilities.
Education and Expertise
Ashish Ranjan holds a Bachelor of Engineering (B.E.) degree in Electronics and Telecommunication from Padmashree Dr D. Y. Patil Vidyapeeth, where he studied from 2005 to 2009. His educational background provides a solid foundation for his expertise in data management and engineering.
Data Warehousing Skills
Ashish Ranjan has engineered a data warehouse utilizing both Inmon and Kimball methodologies, demonstrating his versatility in data warehousing approaches. He employs a diverse set of tools and languages, including Talend, Informatica, Oracle, Redshift, PL/SQL, and SQL, to develop high-quality, scalable, and high-performing systems.
Data Modeling and ETL Framework Development
Ranjan possesses extensive expertise in various data modeling techniques, including conceptual, enterprise, logical, and physical data modeling. He is responsible for the design and development of an ETL framework, ensuring efficient data processing and management.
Technical Proficiencies
Ashish Ranjan has hands-on experience with modern data technologies, including AWS, the Hadoop ecosystem, Python scripting, and Spark. He also has significant experience in performance tuning of data warehouses, focusing on query optimizations for Oracle and Redshift.