Chitrakshi Sharma

Project: myWizard & GenWizard

• Led the migration of over 2,000 servers from CentOS 7.X to Alma 9.X using AWS services (EC2, Lambda, Route 53), and Python automation, resulting in $1M in annual savings. Developed Lambda functions for CRUD operations and API integrations, streamlining data handling. Automated workflows and optimized migration tasks through Python scripting. Also designed and implemented data insertion pipelines from Azure to DynamoDB on AWS, using Lambda functions.

Project: Diageo

• Leveraged Azure Databricks and SQL to design optimized data solutions, translating complex business requirements into high-performance data pipelines. Led the development of KPIs and dimensional models, ensuring efficient data delivery within strict timelines. Collaborated with both business and technical teams to align data solutions with client needs, managing stakeholder expectations to drive successful project delivery.

Project: ADM

• Analyzing complex source-to-target mappings and identifying data gaps, errors from systems like SAP, JDE, SAGE, SPECNET, and Oil-Soft. Skilled in building end-to-end data pipelines, conducting data validations, and working with Azure Synapse for data modeling, including designing dimensions, facts, and schemas for visualization.

• Developing serverless architectures with Python, including building microservices from scratch, and using Lambda functions. Utilized microservice communication and worked with tools like DynamoDB, phpMyAdmin, and JIRA for project management and database handling. Assisted in the estimation of project scopes and timelines during planning phases.

• Worked on the Customer Experience Dashboard as part of the client solutions team, focusing on defining functional requirements for enhancements and bug fixes. Automated backend processes with Python jobs, built adapters for MongoDB data handling, and developed reports by tracking daily and weekly build processes. Created webhooks with RESTful APIs, and followed Agile methodologies to ensure timely delivery. Communicated with clients and coworkers about analysis results.