• Design, implement, and optimize distributed data systems using technologies like Kafka, Flink, Spark, and Delta Lake. • Build and maintain low-latency, high-throughput pipelines capable of handling billions of events per day. • Translate business requirements into robust, scalable architectural patterns, integrating best practices across data modeling, orchestration, data governance, and observability. • Write high-quality, maintainable code and establish patterns that raise the engineering bar. • Collaborate in code reviews and mentor other engineers in software craftsmanship. • Help bridge traditional machine learning workloads with modern AI-based decision systems. • Work cross-functionally with Product, AI, and Software Engineering teams to drive platform adoption.

• Join a cross-functional product team supporting Government Logistics • Develop, validate, and deploy statistical and machine learning models • Design and build data pipelines that integrate authoritative Government systems • Translate ambiguous mission questions from government leaders into analytical problems • Productionize models within government environments complying with DoD RMF and controls • Document methodology for government stakeholders to defend model-informed decisions

• Deploy new data pipelines • Design & build data observability platforms and metrics • Build metadata driven pipeline solutions • Monitor and optimize data transformations • Build third party data integrations

• Perform migration activities of Alteryx workflows to AWS; • Develop and refactor data pipelines using AWS Glue; • Adapt processes and business rules to a cloud-native architecture; • Ensure the quality, performance, and scalability of pipelines; • Provide technical support to the team with specialized Alteryx expertise; • Participate in the analysis, documentation, and optimization of ETL processes.