Vikram Sharma
About Vikram Sharma
Vikram Sharma is a Data Engineer - I at LatentView Analytics in Chennai, India, with a strong background in data migration and transformation. He has successfully led significant projects, including cloud migrations and data source integrations, while achieving high accuracy and efficiency in his work.
Work at LatentView Analytics
Vikram Sharma has been employed at LatentView Analytics as a Data Engineer - I since 2022. In this role, he has taken ownership of the code conversion process, achieving an error-free conversion rate exceeding 98%. He has also led a significant on-premise to cloud migration project, managing 20 TB of data, 500 tables, and over 200 views. His contributions include migrating more than 15 data sources to Snowflake, utilizing Fivetran, AWS Services, and custom scripts. Additionally, he developed a discovery module in the value proposition tool, which has a 95% success rate in identifying and resolving issues within existing schemas.
Previous Experience as Dotnet Developer
Before joining LatentView Analytics, Vikram Sharma worked at the Directorate of Information Technology in Tripura as a Dotnet Developer. His tenure lasted from 2021 to 2022, where he contributed to various projects for a period of four months. This experience provided him with foundational skills in software development and programming, which he has since applied in his current role.
Education and Expertise
Vikram Sharma completed his Bachelor's degree in Computer Science Engineering at The Neotia University from 2018 to 2022. Prior to this, he attended St. Stephen's School, where he achieved his Secondary Education - ICSE from 2014 to 2016 and Higher Secondary Education - ISC from 2016 to 2018. His educational background has equipped him with a strong foundation in computer science principles and practices, which he applies in his professional work.
Data Management and Analytics Skills
Vikram Sharma has demonstrated expertise in data management and analytics. He has managed the transformation and cleansing of over 1 billion records using AWS Glue ETL, implementing Glue PySpark scripts for efficient data preprocessing. He has also developed custom DBT models to facilitate seamless data transformation and modeling across various data layers. His ability to generate detailed investment analytics reports includes performance tracking, attribution analysis, and exposure reporting.
Technical Contributions and Innovations
In his current role, Vikram Sharma has implemented a comprehensive 5-step validation module using the DBT framework to ensure data and object integrity throughout migration processes. His technical contributions have significantly enhanced the efficiency and reliability of data handling within the organization, showcasing his commitment to maintaining high standards in data engineering.