Andrew Ripple Email & Phone Number

Phoenix, Arizona, United States

Denver, Colorado, United States

- Contributed to the design and implementation of a new serverless, cloud based ETL (Extract, Transform, Load) system which beat out internal competition to become the sole provider of TV metadata to downstream clients- Wrote complex Python scripts to deliver data to internal clients via ElasticSearch, files (XML, JSON, CSV), and Kafka- Implemented MYSQL triggers and procedures in Aurora DB, and utilized temporary tables for data processing in Python scripts- Designed large, multi-level Argo workflows with interdependent processes to deliver data to downstream clients daily- Expanded role as a team leader by taking ownership of projects and communicating directly with internal clients- Attended and contributed in software application design meetings with leaders of other internal teams- Helped onboard new team members by performing knowledge transfers of important concepts- Created a React.JS application for internal team use only, iterating on its design and functionality based on feedback (CSS, HTML)

Denver, Colorado, United States

- Quickly became advanced in Python/MYSQL and knowledgeable with basic Perl programming- Worked with technologies such as Docker, Kubernetes, Argo Workflows and a variety of AWS services (S3, Secrets Manager, Aurora DB)- Updated vital, production Perl processes to Python3 while improving code architecture and performance (Up to 20x faster)- Identified major issues with existing production processes and designed/implemented practical solutions- Helped design the re-architecture of the existing TV metadata pipeline from EC2/Hadoop/MapR to a Cloud-Based infrastructure with AWS- Worked collaboratively with other software teams to deliver important TV metadata to downstream customers

American Fork, Utah, United States

- Member of the Critical Problem Resolution team (High priority customer facing issues)- Fixed high priority software issues by using log files to trace back error messages to specific sections of the source code- Improved slow Python script performances by analyzing runtime performance and rewriting problematic/slow functions- Visualized/Created live Grafana dashboards that displayed the current HTTP status codes being sent between Sling and all customer devices (Alerts included for high thresholds)