Aditya Goenka has extensive work experience in the field of data engineering and solutions architecture. Aditya is currently working as a Senior Data Engineer at Onehouse since March 2023. Prior to this, they held the role of Resident Solutions Architect and Senior Resident Solutions Engineer at Databricks from January 2022 to March 2023. Aditya also worked as a Senior Data Engineer at Guy Carpenter from October 2019 to January 2022. Aditya gained valuable experience as a Technical Lead at Tavant from June 2017 to October 2019, where they led a team in delivering a Realtime pipeline and expanding vendor operations. Aditya also worked as a Technical Lead at Tavant from January 2015 to June 2018, where they designed fault-tolerant job orchestration and proposed architecture for batch Spark jobs. Aditya started their career as a Senior Software Engineer at Infosys from March 2012 to January 2015, where they were involved in the development of a Big Data Edge platform and migration of data for analytics jobs.
Aditya Goenka completed their Bachelor of Technology (B.Tech.) degree in Electrical, Electronics and Communications Engineering from IET ALWAR from 2007 to 2011. Aditya then pursued a Master of Technology (MTech) degree in Information Technology from the Birla Institute of Technology and Science, Pilani from 2015 to 2017.
In terms of additional certifications, Aditya obtained the following certifications:
- Databricks Certified Data Engineer Professional from Databricks in December 2021
- Databricks Certified Associate Developer for Apache Spark 3.0 from Databricks in February 2022
- Databricks Certified Data Engineer Associate from Databricks in February 2022
- Academy Accreditation - SQL Analyst Associate from Databricks in February 2022
- Academy Accreditation - Databricks Lakehouse Platform Essentials from Databricks in January 2022
- Employee Accreditation - Lakehouse with Delta Technical Enablement from Databricks in January 2022
- CCA Spark and Hadoop Developer from Cloudera in February 2018
- Developer Certification for Apache Spark from Databricks in January 2017
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