Bike Parts Data Pipeline Development

Built a robust data pipeline that efficiently collected and organized data on available bike parts in preparation for the BikeCheck mobile app. The pipeline was designed to support future integration with the app, ensuring that accurate and real-time inventory data would be available once the app was built. Key responsibilities and achievements include:

Designed and implemented a scalable data pipeline using Python for data aggregation.
Developed ELT and ETL processes to ensure accurate data collection, transformation, and loading into storage systems.

Utilized AWS Lambda to automate the data pipeline processes, ensuring real-time data flow.
Stored data in AWS S3 and DynamoDB for quick retrieval and scalability.
Collaborated with cross-functional teams to ensure seamless future integration with the mobile app.
Ensured the pipeline was scalable to accommodate future growth in data volume and app usage.