- Designed and built a cost-efficient data lake utilising Amazon S3 and Apache Iceberg for ingesting time-series data in Apache Kafka in order to generate monthly reports on the data with Amazon Athena, resulting in a 90% reduction in time taken to generate reports. Infrastructure deployment was automated using Terraform and GitLab CI/CD.- Worked in a cloud migration project, securely migrating data and infrastructure from Azure to AWS using Gitlab CI, Terraform, Amazon Lambda, Amazon ECS, Prometheus and Grafana.- Led a small team of developers in building and optimizing multiple big data connectors for an open source ETL tool using Python, Poetry and Pytest.- Build and manage data warehouses in AWS, handling data transformations, secure storage, and data flow using Airflow, S3, RDS, Redshift, Athena, and Glue; visualized data and created reports with Amazon QuickSight.- Developed and deployed a scalable Python application on AWS, utilising Docker, FastApi, and Github Actions for continuous integration/continuous deployment (CI/CD), with AWS Lambda and API Gateway for enhanced application interfacing.

- Implemented robust backend applications with Docker, FastAPI, and PostgreSQL.- Handled data preprocessing and analysis, and built machine learning models using pandas, matplotlib, seaborn and scikit-learn.- Administered workflow automation and container orchestration through Airflow and Kubernetes, ensuring scalable and robust data operations.

- Semester 1: Assisted with an introductory Python course, guiding students through basic programming concepts and simple project implementation.- Semester 2: Supported a more advanced class, focusing on implementing algorithms and data structures in Python. Helped students tackle complex projects and enhance their problem-solving skills.- Provided feedback on student projects, focusing on code efficiency and practical skills.