Working in Enterprise Platforms under the Delivery Experience tower

• Worked on a set of Python AWS cloud deployment tools used in the Jenkins enterprise

pipeline to meet compliance and security requirements

• Created pipeline failure alert system that leveraged pager duty and SQL through Splunk/Snowflake

• Tools maintained were run tens of thousands of times per day to deploy resources to AWS

• Implemented AWS service deployment tool instrumentation improving error analysis by 81.4%

• Developed shift left policies using Rego to automate detecting failures earlier in the pipeline execution

Worked in Back-End Web Development

• Implemented new data system using Python to improve ingestion runtime through Amazon Kinesis data streams and Grafana framework

• Rebuilt large scale legacy systems to integrate into newer Django framework

• Maintained zero-downtime deployment systems through Jenkins

• Developed and maintained infrastructure using AWS services (EC2, RDS, DynamoDB, Cloud-

watch) and containerization using Docker

• Participated in on-call and incident remediation and triage

• Developed and maintained Data Warehouse ETL tools in python for data ingestion and data

analysis

• Created RESTful API using Django which enabled efficient access to critical imaging and

measurement data used by our research team

• Create data retrieval web application fronted by Javascript framework and Bootstrap

• Built imaging data ingestion pipeline using a tiling algorithm allowing faster and more efficient retrieval and analysis

• Maintained CI/CD pipeline and deployment on AWS servers using Ansible

Work to significantly improve data curation and data ingestion processes for lab and field data through building and maintaining Data Warehouse ETL tools in python