• Advised on testing strategies, project structure, and packaging for engineering + analytics

• Defined continuous integration workflows and architecture for Airflow and Snowplow Analytics

• Guided the transformation of a lift-and-shift AWS environment to “cloud-native” services

• Optimized AWS resource use for a ~40% improvement in efficiency

• Migrated dozens of legacy processes to monitored and tested Python ECS/Lambda services

• Tailored Fastly/Varnish VCL for aggressive caching

• Participated in pair programming to address architectural deficiencies and debug issues

• Designed ETL workflows involving Airflow, AWS Kinesis, Luigi and AWS Redshift

• Engineered an “audio-pipeline” to analyze MP3 metadata for IAB-compliant podcast metrics

• Utilized AWS Kinesis to access near-real-time streams of audio listening metrics

• Documented style guides, project templates, and best practices for Python developers

• Introduced container orchestration and microservice architecture through AWS ECS

• Maintained all infrastructure as version-controlled code utilizing Terraform and Docker

• Implemented robust monitoring with AWS CloudWatch, ELK, Graphite, Sentry, and New Relic

• Mentored engineers on creating local, test-driven development workflows

• Developed new Python services including an authorization gateway and a “serverless” image resizer