Jobs · Engineering · California

System Architect

R Systems · Sacramento, CA · 1 mo ago
EngineeringFull-time

Mandatory Qualifications

  • A minimum of ten (10) years of IT experience with expert-level skills in enterprise architecture design, data modeling, and implementation for data warehouse systems and advanced data analytics platforms.
  • A minimum of three (3) years of experience designing architecture that integrates Generative AI capabilities into Business Intelligence and Data Warehouse platforms.
  • At least five (5) years of cloud architecture experience (such as Azure, AWS, or Google Cloud Platform), including deployment strategies and the use of infrastructure-as-code tools such as Terraform.
  • At least five (5) years of experience leading cross-functional technical teams, providing mentorship, and driving technical excellence in complex enterprise environments.
  • Five or more (5+) years of experience in designing and implementing secure, scalable integration architectures for complex enterprise environments, including APIs, microservices, event-driven systems, and data integration.

Desired Qualifications

  • Five or more (5+) years of hands-on experience with C# / Python, SQL databases, and advanced SQL queries.
  • Five or more (5+) years of experience developing comprehensive technical documentation, including architecture diagrams, design specifications, standards, and best-practice guidelines for enterprise-scale systems.
  • Three or more (3+) years of experience with Snowflake or AWS Redshift.
  • Three or more (3+) years of experience of using Power BI to create data analytics dashboards.

Job Summary

This role will lead multiple concurrent technical initiatives of integrating AI capabilities to data warehouse platforms, oversee end to end solution architecture, and ensure all technology implementations align with client enterprise architecture standards, AI policies, security policies, and business objectives. The candidate shall have advanced expertise in AI technologies, data warehouse, cloud platforms, data engineering, machine learning, and integration best practices, and will act as a trusted technical advisor to technical teams, business partners, and Executive leadership.

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