At Muon, we're helping fight climate change by building world’s most capable Earth-sensing satellite platform and data processing platform to go with it.

I help oversee the technical direction of Vida, with a focus on the backend. As an individual contributor, I'm also able to spend time solving specific problems, including:

• creating our local development environment for microservices (see docker-local-dev project)

• establishing and running our technical review process. We cover everything from KPIs and product requirements, to system architecture, to API specifications.

• helping as we continue to upgrade, migrate, and simplify our technical systems

• making significant contributions to our backend Django and Flask applications

• helping identify, root cause, and fix performance bottlenecks

Some of the key technologies I work with on a daily basis include: Python, Django, Kubernetes, Helm, Terraform, GCP, BigQuery, OpenAPI, Datadog, and PostgreSQL.

(Note: Our career ladder was consolidated in 2021, and Sr. Staff SWE remapped to Staff SWE)

From Sept. 2018 - Aug. 2020, I oversaw both our Data Science team and our Infrastructure team. As we grew, I focused on just the Infrastructure team.

• Transitioned our Data Science team from focusing on analysis to Machine Learning, and helped them make an impact directly on our users. We launched several models, including the recommendations on the Home screen of the app, an enhanced provider matching algorithm, and a meal feedback and recommendation system.

• Established our Infrastructure team, allowing backend engineers to work more closely together and define a long term vision, instead of being pulled from project to project.

• Helped to define much of the hiring process across all of Engineering, while hiring across all different skill levels on my own teams.

During my first year, I focused primarily on helping build key components of our data infrastructure

• Established the "Foundational Metrics" for the company, defining key business KPIs like Active User

• Integrated a feature flagging and experimentation platform (split.io) into our culture, helping improve reliability and allowing statistically validated experimentation for the first time.

• Built our tracking pipeline (using open source Snowplow), and established the schema review process

• Built our first version of a HIPAA compliant Data Warehouse using BigQuery, and a system of views to keep user data isolated and protected