Durai Parvathi Nathan
About Durai Parvathi Nathan
Durai Parvathi Nathan is a Senior Data Engineer with extensive experience in data integration and cloud migration. He has worked at BMO Capital Markets and Tata Consultancy Services, and currently contributes to Next Pathway Inc. in Toronto, Canada.
Work at Next Pathway Inc.
Durai Parvathi Nathan has been employed at Next Pathway Inc. as a Senior Data Engineer since 2021. In this role, he focuses on leveraging his extensive experience in data engineering to support the company's initiatives. His responsibilities include designing and implementing data solutions that enhance data integration and processing capabilities.
Previous Experience at BMO Capital Markets
Prior to joining Next Pathway Inc., Durai Parvathi Nathan worked at BMO Capital Markets as a Senior Data Engineer from 2014 to 2021. During his tenure in the Toronto, Canada Area, he played a significant role in developing processing layers using Hive, Spark, and Pentaho for enterprise capital market consumers.
Background at Tata Consultancy Services
Durai Parvathi Nathan began his career at Tata Consultancy Services as a Senior Software Engineer, where he worked from 2010 to 2014 in India. This position provided him with foundational experience in software engineering and data management, which he later applied in his data engineering roles.
Education and Expertise
Durai Parvathi Nathan earned his M.Sc. in Information Technology from Dr. M.G.R Educational and Research Institute, studying from 2006 to 2008. He has developed expertise in creating Hadoop framework packages for data integration and has extensive experience in designing and implementing data lakes using AWS EMR and Spark.
Technical Skills and Specializations
Durai Parvathi Nathan specializes in converting Hive data definitions and manipulations to Snowflake and Azure Synapse. He is skilled in designing and documenting conceptual and logical architectures for cloud migration projects. Additionally, he has led proof of concept initiatives to evaluate the feasibility of traditional and Big Data reporting tools with data lakes.