■ Added exactly-once messaging semantics to a client’s Socket.io implementation, enabling complex and soft real-time debugging of hardware electronic signals.■ Migrated client charting software from React Charts to Apache ECharts, enabling visualization of high-volume charts to scale from the previous max of ~250 updates/second to over 30,000/second.■ Creating platforms, tooling, and marketing content enabling tech-companies to better engage their customers. Terraform providers, software prototypes, and technical blog posts included. Reference: https://bonsai.io/blog/introducing-bonsais-terraform-provider-for-elasticsearch-and-opensearch■ Advising clients on software design and cloud architecture challenges, helping to build and scale their existing software projects.■ Enabling clients to deploy, manage, and analyze data from a suite of Raspberry Pi Pico based photoelectric sensors via a cross-platform mobile application.■ Added GitHub Actions CI processes to deploy client applications to AWS ECS and AWS Cloudfront via tagged releases.■ Technologies: Ruby on Rails, Flutter, Go, Python, TypeScript, Tailwind CSS, AWS, Terraform, Ansible

■ Worked with Hack Club Bank for fiscal sponsorship/501 (c)(3) status! Hack Club Bank is a project by The Hack Foundation (d.b.a. Hack Club), a 501(c)(3) nonprofit (EIN: 81-2908499). ■ Helped a number of founders get from zero to one, and one to many■ Check us out @ https://relaunchcommunity.org

■ Built two plugins (https://github.com/momer/nutch-selenium and https://github.com/momer/nutch-selenium-grid-plugin) one of which was merged into the trunk 1.10 branch (https://issues.apache.org/jira/browse/NUTCH-1933).

■ Improved accuracy and reduced management-overhead of data-warehouse synchronization by implementing near-realtime streaming Change Data Capture (CDC) with AWS SNS, SQS, DMS, S3; Snowflake Streams, Tasks, External Tables/Stages, and Pipes; via Terraform and Gitlab CI/CD.■ Worked with data science team to restructure, refactor, and implement unit, functional, and integration tests on all projects, which directly led to an 85% aggregate speed-up of all machine learning model training.■ Eliminated categories of data disparity issues by refactoring data warehouse structure using DBT best-practices and introducing database migrations, data quality tests, and data snapshots (SCD2).■ Architected a machine learning platform at the scale of millions of trained models/week, which leveraged Temporal, Go, AWS Lambda, AWS ECS, and GRPC while maintaining the legacy kubernetes-based solution.■ Technologies: Python, Go, AWS, Snowflake, Terraform, DBT, Apache Airflow, GRPC, Temporal

■ Worked hands-on with a team of data engineers unfamiliar with Ruby on Rails through a refactoring of a legacy Ruby on Rails based data integrations, transitioning a number of data sources from MongoDB to PostgreSQL.■ Taught and mentored teams of data scientists and engineers through client-facing projects including custom data integrations; infrastructure deployment; and machine learning model training, deployment, and orchestration.■ Led client/stakeholder discussions and discovery processes which ranged from high-level project proposals to technical implementation details and timeline estimates, ensuring that the projects proposed aligned to the business problems to be addressed.■ Technologies: Ruby on Rails, Go, Python, PostgreSQL, Vue.js, AWS, Terraform

■ Architected, developed, and deployed data lakes and machine learning pipelines on AWS, using technologies including VPC Networking & Security, Lambda, RDS, EMR, and SageMaker, managed and automated by Infrastructure as Code tools like CloudFormation, Terraform, Kubernetes, Helm, and Apache Airflow.■ Uncovered and eliminated multiple advertising platform inefficiencies through log analysis, which led to recurring efficiency savings of over $10MM/year across all programmatic media clients.■ Integrated more than 50 new data-sources into a legacy Ruby on Rails based data ingestion and reporting platform.■ Led the definition and adoption of modern software engineering practices, helping to improve the maintainability, durability, and extensibility of C-K’s software through architecture, automation, and testing.■ Technologies: Ruby on Rails, Go, Python, Vue.js, PostgreSQL, AWS, GCP, Terraform, Apache Spark, Kubernetes

■ Integrated a Data Management Platform (DMP) across all programmatic media and media planning teams.■ Stabilized and refactored existing data ingestion infrastructure, improving analytics capabilities.■ Created budget management application responsible for >$50MM/year in advertising dollars.■ Developed and deployed analytics pipelines and user interfaces for digital advertising data and resulting analyses, including event-level log data from ad servers, demand side providers, and fraud detection providers.■ Technologies: Ruby on Rails, Go, Scala, Apache Spark, Ember.js, Vue.js, PostgreSQL, Docker

■ Created a Ruby on Rails based dynamic financial tracking, estimation, and collaboration web application.■ Developed a large-scale web crawling and machine learning platform and accompanying analyses tying client business data to granular media ad serving data, demonstrating our marketing campaign effectiveness.■ Created a machine-learning pipeline to contextualize millions of web-pages, and serve their top-n keywords at low-latency (sub-40ms) to millions of requests/day.■ Created the world's first large-scale browser-based web-crawler as part of a product-build to extract and contextualize content from web pages.■ Technologies: Ruby on Rails, Go, Scala, JavaScript, PostgreSQL, Apache Spark, Apache Solr, Docker, GCP

■ Worked on Cinnamon Toast Crunch & Brand Initiative accounts, interfacing directly with General Mill's Brand Teams, MRM NY Production, and other departments to make sure that production and marketing campaigns are effective, on time, and on budget.