Led the development of application service utilizing micro-service architecture, AWS Cloud Deployment Kit, CloudFormation, REST APIs.

Implemented and utilized Apache Airflow setup, Python backend to orchestrate jobs ensuring reliable data processing.

Enhanced user interface designs and provided solutions to potential challenges in product resulting in its success.

Collaborated with cross-functional teams to elicit requirements designing and developing forecasting models.

Automated infrastructure through code to enhance security and streamline data handling mechanisms across various sources and destination to support multiple data formats by serialization and de-serialization.

Provided guidance and mentorship to Engineers and Business Analysts, ensuring adherence to best practices and facilitated projects success.

Crafted tools, automation scripts, and documentation to enhance engineers experience in handling external customer interactions.

Diagnosed network issues and recommended optimal cloud migration strategies to enhance the efficiency of customer applications.

Integrated and tested AWS SDK and AWS CLI with a wide variety of services like Lambda, API Gateway, Step Functions, EC2, VPC, S3, SNS, SQS, AppSync (GraphQL), Rekognition, Lex etc to architect diverse customer use cases.

Actively performing Root Cause Analysis (RCA) identifying and helping resolve issues in the services.

Advised on optimal distributed architectural solutions with AWS cloud to address customers unique business usecases.

Created Deep learning models using Neural Networks for image classification using Python, TensorFlow Object Detection APIs, CNN, and Colab Jupyter-Notebooks.

Developed Shell scripts to set up, and troubleshoot Intel OpenVINO SDK and network in the Linux environment.

Applied creative Problem-solving skills and effectively communicated with a team of three people with different backgrounds to solve challenges and create a functional prototype.