AI Enterprise Data Automation Senior Consultant

Design and prototype an agentic SDLC model, where AI assists in building data pipelines, semantic models and other data engineering components integrated with Jira-based work management and human oversight. Participating in design sessions, defining solution architectures, and identifying high-value opportunities to automate processes across the data ecosystem.

AI Enterprise Data Automation Senior Consultant
Onsite Omaha, NE
Up to 20 hours/week

We are seeking a Senior Consultant to support enterprise data process automation through engineering, architecture, AI, and lead expertise. This role will contribute to solution design, uncover automation opportunities, and support implementation within the enterprise data ecosystem.


Key Areas of Responsibility:

Lead design activities, contribute to the automation strategy, and identify opportunities for process improvement and other value-add outcome across the enterprise data landscape. Responsibilities include developing prototypes, supporting implementation, defining agentic SDLC patterns, and overseeing delegated execution where appropriate. Mentor team members, transfer knowledge, and document work products, progress, and recommendations in a clear and usable form.
 

• Engineering & Architecture
  Shaping the technical foundation for automation. Participating in design sessions, defining solution architectures, and identifying high-value opportunities to automate processes across the data ecosystem.
• Data Process Automation
  Targets the automation of core enterprise data functions. Improve efficiency and consistency in data quality management, data access, security, metadata management, platform operations, and governance workflows.
• Agentic SDLC Automation
  Introduces AI-enabled software development practices. Design and prototype an agentic SDLC model, where AI assists in building data pipelines, semantic models and other data engineering components integrated with Jira-based work management and human oversight.
• Mentoring & Enablement
  Ensure sustainable capability building within the team. Mentor data engineers and governance personnel, supporting onboarding, and closing knowledge gaps in automation, AI engineering, and context engineering.