Summary
Justin Kraus is a Senior Data Engineer based in New York with eight years of experience building large-scale, production-ready data pipelines and visualization-driven insights. He combines an MS in Data Visualization with deep hands-on expertise in Python, Spark, SQL, Airflow, and AWS to deliver both real-time streaming and batch architectures that drive measurable cost and performance improvements. At Condé Nast he optimized Databricks clusters and S3 storage to cut AWS spend while maintaining high throughput, and he has productionized services including an email validation API deployed to EKS with Terraform and GitHub Actions. Before focusing on data engineering he led capital planning and regulatory programs at major banks, bringing a strong discipline for governance, auditability, and cross-functional stakeholder alignment. Now at Dotdash Meredith, he applies that blend of financial rigor and design-minded visualization to translate complex datasets into actionable products for technical and non-technical audiences. Colleagues value his ability to bridge regulatory-grade data practices with modern cloud-native ETL and observability patterns.
8 years of coding experience
18 years of employment as a software developer
Master of Science - MS, Data Visualization, Master of Science - MS, Data Visualization at Parsons School of Design - The New School
Bachelor of Science (BS), Finance, Entrepreneurship, Bachelor of Science (BS), Finance, Entrepreneurship at Northeastern University