Teams at Veriday

Administer and optimize an enterprise Snowflake platform for a banking client. Responsibilities include security and RBAC, warehouse configuration, query and cost optimization, incident response, database hygiene, AWS integrations, automation, monitoring dashboards, documentation, and collaboration on platform architecture and reliability improvements.

Design, build, and operate scalable production machine learning platforms and MLOps systems. Own the ML lifecycle, including feature engineering, deployment, monitoring, governance, retraining, model versioning, and real-time inference. Build Feature Stores, Model Registries, CI/CD/CT pipelines, and data pipelines across cloud and streaming environments. Ensure performance, reliability, observability, security, regulatory compliance, and explainability while collaborating with data, software, and business teams and mentoring junior engineers.

Provides technical leadership for enterprise backend applications using Java, Spring, AWS, and Terraform. Designs cloud-native microservices, REST and SOAP services, and infrastructure as code; guides architecture and development best practices; collaborates with stakeholders; reviews code; mentors engineers; and resolves complex production issues. The role is hybrid in Cincinnati, Ohio, with three days per week onsite and requires 9+ years of Java/J2EE experience.