Manager, Data Systems
Intradiem
| Company | Intradiem |
| Category | Data & Analytics |
| Location | Remote |
| Remote | Remote |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 22 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Intradiem is reinventing customer service for everyone by helping organizations connect people, technology, and real-time action to create more agile operations and more human experiences.
Who We Are Intradiem is the leader in Dynamic Workforce Orchestration. We help organizations create service agility by connecting people, technology, and real-time data to improve customer experiences and support employees. We believe automation should empower humans, not replace them.
What We Do Our platform turns real-time insights into real-time action. By orchestrating work across customer service teams, we help organizations break down silos, adapt instantly to changing demand, and operate more efficiently without losing the human touch which is essential to customer service.
How We Work We solve real operational problems alongside our customers. Our approach is practical, collaborative, and focused on outcomes. We listen first, build with purpose, and create technology solutions that work in the real world.
Our Culture We’re proud to be a people-first company. We treat employees with trust, respect, and flexibility because great customer experiences start with supported teams. We move fast, collaborate closely, and believe the best ideas come from empowered people working together.
Our Values
We encourage our employees to contribute time and energy to causes that help improve the people and communities in which they live and work. We are guided by three core values:
Servant's Heart —We believe in caring enough about other people to understand what their problems are and placing the needs of colleagues, customers, and others over personal objectives.
Craftsman's Attitude —We believe in taking pride in the work we do and creating solutions that actually solve the problem at hand (and trying again if the first attempt doesn't do the trick).
Growth Mindset —We believe that progress comes from curiosity, openness, and perseverance. We welcome feedback, embrace change, and push beyond comfort zones to unlock new potential for ourselves, our teams, and our customers. Enterprise Data Architecture & Execution
Execute Intradiem's enterprise data strategy and roadmap, ensuring data architecture supports AI transformation and advanced analytics capabilities.
Implement and maintain comprehensive data governance frameworks covering data quality, lineage, access controls, privacy, and regulatory compliance requirements.
Support defining enterprise data standards, cataloging, metadata management, and self-service analytics capabilities that democratize data access while maintaining security.
Partner with IT and Legal teams on data privacy frameworks, security architecture, and regulatory compliance.
Business Intelligence & Analytics Execution
Support the buildout and maintenance of business intelligence solutions that drive data-driven decision making across all functions with production-grade reliability and monitoring.
Build automated reporting systems and KPI tracking mechanisms with real-time monitoring capabilities.
Collaborate with business stakeholders to translate requirements into technical data solutions and reporting frameworks.
Troubleshoot data quality issues and implement systematic solutions to ensure data integrity and reliability.
Serve as primary point of contact with our data infrastructure partners, managing relationships and technical requirements.
AI-Ready Data Infrastructure
Lead and coordinate the transformation of enterprise data architecture to be AI-native, ensuring data is structured, accessible, and optimized, partnering with and enabling the AI Center of Excellence rather than executing in isolation.
Establish API frameworks and data integration patterns that enable real-time AI model access to enterprise data.
Create data sandboxes and experimentation environments for AI use
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