Jobs at Spring Financial

Build and maintain secure, scalable data pipelines and platform components using AWS, Snowflake, dbt, and Airflow. Modernize legacy data flows, integrate batch and streaming sources, improve testing and observability, and support self-service analytics. Develop AI-enabled capabilities such as anomaly detection and automated tagging. Partner with Finance, Risk, Product, Analytics, ML, and Engineering teams to define requirements, meet SLAs, ensure data governance, and deliver reliable infrastructure end to end.

Build and deliver full‑stack, production-grade features end-to-end. Design, implement, test, deploy, and operate services on AWS. Use AI-assisted tools responsibly, maintain CI/CD and observability, participate in on-call and incident response, and mentor junior engineers while collaborating with product and design.

Design, build, and maintain dimensional data models, curated data marts, and a governed semantic layer using Snowflake and dbt. Optimize SQL queries for performance, validate models with tests and observability, troubleshoot production data issues, and partner with stakeholders to define KPIs. Use AI-assisted tools responsibly, enforce CI/CD and version control, and mentor junior analytics engineers.

Lead Spring's combined platform and systems engineering function, owning product and corporate technology. Drive an AI-native platform strategy using agents for provisioning, remediation, and support. Ensure reliability, observability, security, CI/CD health, SLOs, and least-privilege identity across systems. Manage engineers and managers, partner cross-functionally, reduce toil through automation, and mentor leaders while owning help desk strategy and governance.