Daniel Egas 👋

- Built an ELT data pipeline by extracting e-commerce data from CSV files and APIs using Python and Pandas, loading it into a SQLite data warehouse, and transforming it through SQL queries forstructured analysis.

- Analyzed key business areas—Revenue and Delivery—identifying popular products, revenue trends, and delivery performance, including the impact of public holidays on order processing.

- Generated actionable insights by correlating various data types and company KPIs, leading to performance assessments and strategic recommendations.

- Visualized findings using Matplotlib and Seaborn, effectively communicating results and trends through data-driven storytelling to support business decision-making.

- Developed a web application with Python and Django that replaced a disorganized manual process for student certification registration, enabling administrators to manage applicants, validate documents, and track eligibility, which streamlined workflows and eliminated information loss.

- Optimized the certification process by automating from submissions, document verification, and record-keeping, resulting in the accurate processing of 800+ certifications annually and a significant reduction in administrative workload.

- Implemented automated report generation in PDF format and integrated storage of all certification records using AWS S3 buckets, ensuring secure, centralized, and easy retrievable documentation.

- Established a CI/CD pipeline to automate deployment and maintenance of the application, increasing reliability, reducing downtime, and ensuring faster iteration of updates.

- Developed a robust REST API using Django REST Framework, enabling seamless interaction between the backend, web frontend, and mobile application, which ensured real-time data communicationacross platforms.

- Implemented core backend functionalities in Python using Django and object-oriented programming principles, successfully managing modules for products, services, orders, reservations, and a rewards system, contributing to a scalable and maintainable architecture.

- I implemented and managed AWS services to deploy and scale applications, leveraging EC2 instances for compute resources and integrating cloud-based databases, ensuring high availability and scalability in cloud environments.

- I used Docker and Docker Compose to containerize web applications, creating reproducible environments that included services for the backend application, PostgreSQL databases, and caching systems like Redis, optimizing portability and deployment across different environments.

- Executed black-box testing to validate system functionality and performance from the end-user perspective, ensuring optimal behavior and stability across multiple scenarios.

- Developed unit and automated tests using Dynatrace, significantly improving the speed and accuracy of the verification process and reinforcing the reliability of key software components.

- Managed and structured detailed test plans in Azure DevOps, defining scope and objectives to ensure systematic and goal-oriented testing aligned with project requirements.

- Reviewed and verified new or updated code to ensure correct functionality, reporting issues or inconsistencies to the QA lead and helping maintain code quality across development iterations.