Vikas Doshi

About Vikas Doshi

With a pivotal role at JPMorgan Chase & Co, my focus lies in innovating big data architectures and implementing strategic cloud solutions that cater to the rigorous demands of the financial sector. Expertise in AWS and Azure platforms empowers our team to automate deployments and refine data processing pipelines, resulting in enhanced operational workflows and system efficiencies. By leveraging professional communication skills and tools like AWS SageMaker, we\'ve crafted scalable data solutions and robust applications tailored for large-scale environments. The ingenuity in our approach to data management and cloud architecture has been instrumental in propelling system optimizations and advancing the strategic objectives of our organization.

Experience

1. Sr Cloud Architect Engineer Developer

   JPMorganChase

   Mar 2019 — Present · New York, NY, US

   Involved in import and export of data from/to Oracle to/from HDFS using Sqoop. Created Sqoop jobs to populate data present in relational databases to hive tables. • Created RDDs/Data Frames using SPARK with Python and used various transformation and action and performed in-memory computation capabilities. • Used Bash and Python, including Boto3 to supplement automation provided by Ansible and Terraform for tasks such as encrypting EBS volumes backing AMIs and scheduling Lambda functions for routine AWS tasks.• Automated deployment of Database/Application servers on AWS ec2 instances & ECS cluster using Ansible & Terraform.• Deployed AWS EKS using customized and hardened AMI via Terraform, and utilized Kubernetes RBAC feature to control access to the cluster• Using configuration management tools such as Puppet and Ansible to ensure consistency, repeatability, and audibility.• Used YARN resource manager to manage the resource in the Hadoop Production/Dev cluster. • Involved in performance tuning of spark jobs using Cache and using complete advantage of cluster environment. • Develop daily/weekly/monthly reports using Business Objects and provide access to the required users for reporting analysis. • Sourcing data from Kafka/Flume to Spark streaming and storing data in HDFS for further analysis • Worked with Cloudera Manager APIs, Rest API on automation.• Exploring with Spark, improving performance and optimization of the existing algorithms in Hadoop using Spark Context, Spark-SQL, Data Frame, and Pair RDD\'s.• Coordinated with testing team for bug fixes and created documentation for recorded data, agent usage and release cycle notes.• Worked on Hadoop Operations on the ETL infrastructure with other BI teams like Tableau.

Education

• Gujarat Technological University, Ahmedbabd

  Bachelor of Engineering - BE

  2009 — 2013