You'll be responsible for ensuring our datasets maintain the highest levels of accuracy, consistency, and observability - implementing comprehensive monitoring, lineage tracking, and self-healing mechanisms that maintain data quality at scale. Your infrastructure will support both analysts / scientists and autonomous AI agents with equal effectiveness, requiring thoughtful interfaces, documentation, and metadata that serve both audiences.In this role, you'll champion a forward-thinking approach to data infrastructure that anticipates the evolving needs of AI systems while maintaining the reliability and performance that business operations demand. You'll help shape our technical roadmap for data systems that will serve as the foundation for our organization's AI transformation journey.Key job responsibilities
- Architect and implement scalable data infrastructure that enables both traditional analytics and modern AI/ML workflows
- Design data models and pipelines that optimize for AI readiness while maintaining traditional reporting capabilities
- Build robust ETL/ELT processes to ingest, transform, and prepare data for varied consumption patterns
- Develop APIs and interfaces that allow AI agents to programmatically discover, access, and utilize enterprise data
- Implement vector databases and embedding storage solutions for AI applications
- Create data quality frameworks that ensure both human and AI consumers can trust the data
- Establish metadata management systems that make data discoverable and understandable
- Collaborate with data science and AI teams to understand their infrastructure requirements
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
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