Experience
2024 — Now
2023 — 2024
Digital Services Expert recruited by the United States Digital Service to advise on the integration of modern software engineering best practices into federal agencies.
• Helped review and launch National Law Enforcement Accountability Database (NLEAD).
• Working across vendors nationally to help define and launch the first Housing and Urban Development's REST API
2023 — 2023
2023 — 2023
San Francisco Bay Area
2021 — 2022
2021 — 2022
San Francisco Bay Area
Senior Software Engineer - Foundations
Technologies and Tools:
• Internal high-throughput low-latency async processing framework (Monster)
• Scala, Ruby/Sorbet, Bazel, Kubernetes
• Protobuf/BSON, gRPC
• Developer Productivity Tools, Legacy Code
• SignalFx, Splunk, EC2
Key Concepts:
• Distributed Systems, Asynchronous Processing Infrastructure
• Cross-Functional Documentation
• Tech Debt Management
• High-Stakes Low-Latency Scenarios
• Functional Programming, Ruby Type Systems
Major Projects:
• Service Migration: Planned and executed a migration with a small team that saved approximately $1M annually.
• Kubernetes Migration: Assisted in migrating an internal service used by 60% of teams at Stripe to Kubernetes.
• High-level Stakeholder Management: Drove organizational clarity during major Strip-wide observability updates.
• Team Processes: Designed and advocated for effective team processes
2017 — 2020
2017 — 2020
San Francisco Bay Area
Technologies and Tools:
• Python, Airflow, Ruby, Rails
• Docker, Nomad, Kafka, Kafka Connect
• Terraform, Git
Cloud and External Services:
• AWS (SNS/SQS, S3)
• Confluent Kafka
• Zendesk, Eligible
Key Concepts:
• Event-Driven Architecture
• Test-Driven Development (TDD)
• Observability, Data Ingestion Pipelines
• 508a Accessibility, PHI and PII Compliance
• Pair Programming
Major Projects:
• Data Mesh Initiative: Led discovery, technology/vendor selection, and tooling to improve support for internal event-driven infrastructure.
• Developer productivity: Created experimentation and monitoring tools to enhance developer productivity.
• Data Model Changes: Implemented organizational data model changes for improved data management.
• Internal Tools: Built tools to streamline patient transitions across customer populations.
• Team Management: Managed team velocity and tech investment/discovery
Education
Oberlin College