More than 10,000 servers were migrated

Bigdata

automated few jobs

Migratedwarehouse data to Azure synapse

Worked close with Microsoft AI team in building innovative Copilot using corporate data and OpenAI Copilot, a project focused on developing an advanced conversational AI system. Applied data vectorization techniques to transform raw data into numerical representations, facilitating advanced analysis and modeling processes. Successfully collected data and ingested data into Azure Data Lake Storage, leveraging it effectively for the development of the AI CoPilot. Applied prompt engineering techniques to optimize the OpenAI chatbot, enhancing its overall performance and user experience. Demonstrated expertise in fine-tuning Azure OpenAI Models using Azure Machine Learning optimizing their performance for specific tasks or domains and ensuring they meet project requirements. Successfully deployed Azure OpenAI Models at scale, leveraging the scalability features. This enabled efficient processing of extensive datasets and supported real-time inference for high-performance applications. Deployed the Copilot backend environment in the Azure sandbox subscription, making it available for demonstration purposes. Established and maintained a comprehensive vector database, incorporating all ingested data for streamlined accessibility and analysis. Efficiently ingested data from Knowledgebase into our Azure environment, generating embeddings for seamless integration with an AI Chatbot. Pioneered the development of a temporary UI for a tech spike using Azure OpenAI, delving into the potential of the platform and exploring its capabilities. Collaborated closely with Microsoft in the OpenAI Hackathon: Hexagon & Microsoft, contributing to the finalization of the Copilot architecture for deployment within the Nexus Azure subscription. Facilitated data acquisition and loading from HTML/PDF sources in collaboration with ZoomIn, enriching the ChatGPT store with diverse and valuable content. Explored and implemented language translation functionalities, enhancing ChatGPTs versatility and enabling multilingual capabilities for improved user interactions. Proficiently built and maintained Docker images, streamlining the deployment process and ensuring consistency across environments. Achievement & Recognition: While collaborating closely with Dr. Horen on this project, I consistently demonstrated exceptional expertise and dedication, earning recognition for my valuable contributions. My efforts were acknowledged for their significant impact on project success and outcomes. This experience further solidified my reputation for excellence in engineering and artificial intelligence technologies.

Closely worked with the Databricks to design and implement data transformation processes, machine learning workflows, and advanced analytics tasks using Databricks. Scalable solution with improved performance, particularly for processing data which in the current situation scattered over many individual simulation result data files. Utilized Databricks machine learning tools to manage more consistently the pipelines of getting the data from the raw simulation results files to the databricks environment. Validated the performance and scalability if needed by extending the test on a largely size data set in Hexagon MI environment. ETL pipeline, CI/CD pipeline, Azure data Factory. Ensured feasibility of abstraction layer between the raw simulation result files and the engineering analytics. Presented the MLFlow architecture design to management, instilling confidence in the proposed solution. Leveraged Databricks ML to design and deploy advanced algorithms and models, effectively processing extensive datasets for valuable business insights. Collaborated closely with internal stakeholders and cross-functional teams, infusing domain expertise into solution approaches. Maintained a proactive approach in keeping abreast of the latest developments within the data science field, expanding technical skill sets, and exploring additional data sources for enhanced analytical capabilities. Validated that the solution can be used for all the different engineering data types. Selection of engineering data types:Time series Integrated Power BI with Azure data services, creating interactive dashboards and reports to provide valuable insights to stakeholders. Played a vital role in establishing and refining data science engineering practice on Databricks, crafting replicable solutions like data products, recipes, and comprehensive project documentation. Developed process flowcharts to streamline workflows and ensure consistency. Achievement & Recognition: Received notable recognition from the customer for achieving highly optimized storage in Delta with significantly enhanced performance.

Engineered a chatbot utilizing Python code and web crawling techniques, employing data extraction and automation methods to deliver superior user interactions. Implemented version control for the web crawler chatbot code by uploading it to Git DevOps, ensuring seamless collaboration and efficient management of code versions.