Delivered multi-account scalable Cloud Datalake solution in AWSo Full solution is delivered using IaC with Zero manual stepso Designed Federated and Centralised data lake storage management solutionso Secured datalake using native AWS services like KMS, VPC, Endpoints, Security Groups and IAMo Developed framework for AWS Lake Formation to manage Multi-Account access managemento Designed mechanism to scan and store metadata for the Datalakeo Deployed CI/CD pipelines in Jenkins for various BAU tasks to control AWS deploymento Streamlined onboarding of new teams on Datalake using in-house developed 25+ SC productso Developed Share and accept framework to share portfolio of products with various teamso Designed and Developed Tag based Access Control Mechanism in Lake Formationo Serverless logging and auditing framework is designed for the datalakeo Zero Defects in Penetration Testing conducted by external vendors twice in past 2 yearso Zero Observations of any access leakage by Barclays Internal Audit Teamo Zero Downtime in past 3 Years for the Datalakeo Trained 6-member support team for BAU tasks of Datalake tenantso Designed Observability Dashboard which provides various metrics like size, utilization, costDesigned multi-accounts credentials vending solutiono Used API Gateway, Lambda, Glue, Lake Formation and S3o Secured datalake by removing direct access of source account to s3.o Secured solution by deploying API Gateway privately, hence no public access allowedo Deployed hub-spoke model, with hub comprising of 2 centrally managed AWS AccountsDeveloped a file transfer utility for streamlining transfers from on-premise servers to S3o Serverless, Scalable Secured and highly resilient solutiono Deployed the utility on on-premise Landing Serverso Implemented logging and auditing using CloudTrail

#Designed, developed and deployed critical automation solutions across various data platforms to simplify complex business processes saving the team manpower equivalent to 3 engineers and reduce user issues by 75%. Examples below.#Developed Housekeeping Dashboard for Hadoop Platform using Django - reduced utilization by 20%#Deployed Hadoop Qouata Utilization service, which is used in storage management/forecasting by stakeholders#Developed an automated Weekly Tenant-wise Platform Utilization Script in python and saved 0.2 FTE#Developed an Excel VBA which provides details of all the Infrastructure under Barclays UK#Developed automated scripts for health monitoring, storage monitoring which helped in achieving 100% uptime of platform and reduced outages from 60/quarter to 0/quarter#Coordinated the migration of legacy SAS 9.2 onto the SAS 9.4 Grid platform, saving about £1 million in licensing and infrastructure cost#Created SAS GRID Platform Utilization Dashboard which transformed the cost planning and forecasting process for the platform from ad-hoc methods to a structured approach. I have executed all aspects of planning and creating AppDynamics Dashboards using Python, ranging from design to deployment. Also received recognition in the Barclays Town Hall from the Chief Data Officer for the initiative

● Proposed a novel solution for the singular integral equation using Chebyshev polynomial approximation● Modeled and computed the solution in Python using analytical properties of Chebyshev polynomials● Verified the solution against accepted solutions and published results in TAFM (Journal Impact Factor – 2.25)

● In charge of creating problem sets and correcting submissions which were critical for the completion of the course● Designed a Python tool to generate unique problem statements to prevent plagiarism● Created an automatic evaluator and integrated with the on-campus LMS, reducing correction time required

• Implemented Total Productive Maintenance on Newly Constructed Fully Automated Line.• Implemented KAIZEN and Poka-Yoke on Various Machines in the Machining Department• Performed Case Studies on Increase in Production by Indirect Methods