+ Managing a team of 12 engineers+ Hire and grow the engineering team with right talent to meet the product expectations+ Work with product managers to deliver engineering roadmap to deliver features for a data engineering product+ Working with senior leaders within the organization to identify and rollout out the engineering priorities and get it delivered in time bound way+ Work closely with DevOps , Testing, Infrastructure and production team to manage smooth execution of entire program+ Work with backend API team to get backend contracts and endpoints delivered in Python django API+ Work with senior data engineers and Principal engineers to get the data engineering pipelines ready on the Spark Databricks platform+ Work with data engineering team to get the streaming capability delivered in the product+ Closely operate with Product manager and application designers to shape the front end features supported in the product+ Closely work with product architect to evolve and integrate new capabilities in the cloud design+ Manage the performance and productivity of the engineering team to meet the product timelines+ Managed offshore and Onshore team for smooth transition of engineering deliverables.+ Made process and team changes to be aligned with overall engineering needs to successfully deliver major features to our client+ Managed an AI project to quickly deliver a POC on LLMs using Azure Open AI

+Lead a team of software developers to build end to end automated solution for PepsiCo business units.+Managed relationship with cross functional business teams and different IT teams cloud infrastructure, cloud security and operations team to deploy various web application and data engineering solution on Azure cloud infrastructure.+Managed communication with executives and higher management to provide the digital solution roadmap for PepsiCo R&D business.+Lead proof of concepts projects with external vendors to deliver value to the business and manage the dollars spend on these projects.+Developed the robotic process automation (RPA) project using UiPath to automate and streamline business process.+Lead a data engineering project to clean, transform and aggregate the PepsiCo Supplier, Ingredient and Plant datasets using Azure Synapse and Databricks, to build analytics and BI solution on top of this datasets.+Automated the entire cloud infrastructure using git repository, Azure DevOps, and CI/CD pipelines to streamline the deployment efforts+ Lead the engineering team by managing the tasks, user stories, features, and sprints on the Azure DevOps board and participated in biweekly demos with the business user to show the progress and get the feedback to build the software product iteratively. +Engaged with data governance team to identify the gaps in the data collection and retrieval system for PepsiCo R&D and accordingly build strategy and processes to improve these gaps and build data visualization and analytics layer on top of this dataset using Power BI+Developed and troubleshooted various cloud infrastructure related issues on the Storage, Networking and Security layer

Engaged with R&D business users and IT to identify the existing gaps in the R&D data collection and retrieval system and accordingly build strategy and processes to improve these gaps. Lead the technology project to work closely with consulting partners to develop prediction model for the PepsiCo seasoning team. Developed Python script to transform and clean the UK snacks shelf-life raw data be feed into the predictive machine learning model. Develop visualization dashboards using Microsoft Power BI tool to contribute toward key matrix on beverages and snacks R&D dataset.Develop machine learning model using natural language processing wor2vec algorithm to process and search unstructured documents.Worked with diversified data engineering and data science team within PepsiCo to build the R&D data warehouse on the cloud environment. Design and deploy the data pipelines to move R&D datasets from different geographical location on premises system of records to data warehouse build on Azure cloud Data Lake environment using Azure data factory and Python scripts on Data Bricks.Developed restful API service to pull data on demand and automated the deployment on Azure cloud infrastructure using CI/CD pipelines.Containerize a PHP web application using docker container service and deployed it on the Azure application service.

+Managed interaction and communication with multiple financial clients Amex, TD and RBC bank to get the business requirements, set priority and design end to end engineering solution to meet business expectation+Managed the offshore technology teams to build digital and data engineering solutions for banking clients

+Managed interaction and communication with multiple financial clients Amex, TD and RBC bank to get the business requirements, set priority and design end to end engineering solution to meet business expectation+Managed the offshore technology teams to build digital and data engineering solutions for banking clients+Developed automation script using Python Pandas library for data manipulation and loading the dataset into relational databases+Worked with data science team to architect, develop and deploy a big data solution to process regulatory dataset for machine learning use case+Lead engineering solution to clean and transform the datasets using Spark and store it in centralized data warehouse for BI reporting use case+Worked with data modeling team to architect the big data solution to process the financial streaming data on the Hadoop cluster and store it in HDFS file system and analyze the data using Hive query and automating the entire workflow using workflow manager +Worked with production team to troubleshoot and fix any infrastructure, networking, or security issues during deployment

• Develop an interactive web forum for students and faculty.• Monitor daily activities such as student appointments, record classroom lectures, updating student records in MS-ACCESS and SalesForce.• Migrate database of students/alumnus from MS-ACCESS to SalesForce.• Assist students and faculties in the Executive MBA and Technology Management Programs.

Developed inventory management system for different machines present in data center using open source LAMP components:Linux operating system, the Apache HTTP Server, the PostgreSQL relational database management system (RDBMS), and the PHP programming language. This is a web application used extensively to monitor the different host's present in the data-center.1) JQuery and java script is used for validations and client side scripting of the web application.2) Git is used for the version control of the web application. 3) Added features such as report generation and written script to interact with different Red Hat Linux machines to get their status and location of the data-center.

1) Interacting with the client for system study, requirements gathering, analysis and scoping; analyzing architecture definition, design patterns & solution for the project and selecting appropriate technologies for development approach. 2) Establishing process setup and monitoring the development; conducting code review, debugging and troubleshooting the application. 3) Managing smooth implementation and testing of the application at client location; extending post go-live and application maintenance support to the client.

Project Details : “Training in TV fundamentals and audio amplifiers”