Worked cross team to create infrastructure needed by Databricks. I created a Databricks pipeline using the Python Spark API, PySpark, and Spark SQL, leveraging Auto Loader for efficient data ingestion from cloud storage to a Unity Catalog table. 
Worked on a larger project, with a Databricks team I collaborated often with. We used templated configurations with Databricks Asset Bundles, to apply infrastructure-as-code principles, and develop and configure the jobs and resources we required across environments. We created pipelines to help us develop the best strategies and solutions for our engineering initiatives. I provided context for both our existing architecture and use cases, participated in pair programming, which further improved my Databricks knowledge.

Implemented an internal ad-network diagnostics platform: defined requirements with users, collaborated on the creation of the ETL pipeline from micro-services to cloud storage, and used Go to expose API endpoints for a React frontend to help surface root causes and prevent costly incidents related to our AdTech stack.

Collaborated with the architecture team on issues related to horizontal scalability.

Utilized Datadog notebooks to provide visibility into services, answering questions from product and other engineers. Also as part of the process for creating custom service dashboards.

During development of a product for non-technical management of streaming platform configurations, I proposed and implemented a simpler alternative architecture. This allowed my team to deploy the service in time for our PI deadline while meeting requirements. These services and their design remain in place today.

Worked on numerous cross-functional teams, with tasks ranging from expediting the migration of services to Kubernetes to creating POC solutions to validate product initiatives.

I provided assistance to team members in their preferred formats, collaborating on any issues they may request help with.

Designed and implemented the company's first scalable cloud-based order and subscription processing system, integrating with Shopify, handling e-commerce intricacies, and categorizing erroneous transactions.

Utilized GCP services (App Engine, Cloud Run, Cloud Tasks) and Splunk for efficient transaction processing, log retention, and attack mitigation, creating custom metrics and alerts.

Developed a full-stack e-commerce platform using Node.js, TypeScript, NestJS, Gatsby, React, and Strapi CMS, including tooling for version migration and content management.

Created and maintained infrastructure as code using Terraform and optimized Dockerfiles for containerization.

Improved developer UX by creating tools to emulate GCP services in local development environments.

Initiated knowledge-sharing practices by documenting processes and leading backend team meetings for demos and discussions.

Utilized MongoDB, becoming a Certified Developer Associate, writing optimized MongoDB aggregation pipeline queries, and designing efficient schemas optimized for our use cases.

Led development of backend services for Nike's templated messaging system, utilizing Node.js, TypeScript, React, AWS (SQS, DynamoDB), and Kubernetes.

Optimized Dockerfiles, configured Terraform, and managed deployments to Kubernetes clusters.

Developed and maintained full-stack Node.js/TypeScript microservices with PostgreSQL, NATS, GraphQL, and React.

Utilized Garden for creating production-like development environments in Kubernetes.

Managed production deployments and releases.

Built tools to improve data quality in ServiceNow's Discovery network mapping solution using Python and JavaScript.

Developed Slack notifications and integrations for operational monitoring and alerting.