- Conceptualized and executed Movable Ink's data strategy, creating innovative platforms and paradigms for internal business users and client-facing product use cases. Building foundational data marts, organized as Kimball dimensional models and Star Schemas.- Collaborated with cross-functional teams to develop and maintain data pipelines, emphasizing ELT processes within a centralized data warehouse on Redshift. Leveraged Go, Python, SQL, and Apache Airflow for efficient implementation.- Led the successful migration from legacy data systems to AWS Redshift, resulting in a monthly cost reduction exceeding $100,000 while maintaining or enhancing data quality and accessibility. Implemented robust dimensional models to make data available for downstream product and business systems.- Spearheaded the creation of a self-service, customer-facing reporting and analytics tool. Built with Ruby on Rails, ReactJs, Postgres, AWS Redshift. Resulting in an 80% decrease in manual custom reporting tickets.- Developed a comprehensive analytics strategy, identifying key metrics and KPIs to drive business insights and inform strategic decision-making.- Established and maintained robust data governance processes and standards, ensuring data accuracy, reliability, and security. Adhered to privacy frameworks such as GDPR and CCPA.- Built a user recommendations engine, using AWS Neptune and Graph data models to allow clients to serve relevant content to their customers

Designed, created and deployed a distributed real time data processing system, processing over 30,000 events per second, providing clients an API for near real-time access to customer profiles. Using GoLang micro-services, Spark Streaming, NSQ, and Cassandra. Wrote Chef cookbooks to manage the deploy process.Developed a system for serving customized javascript mappings of clients sites, in a way that is easily scalable and deployable with minimal setup and client intervention, using NodeJS.Provided actionable and accessible insights to customers through daily EMR jobs using Hive generated reports from a data pipeline producing nearly 1 billion rows of data a day. Provided clients with the ability to run customizable audience forecasting via a Rails dashboard, using Hive and Python.