Principal Data SRE

Working at the intersection of AI platforms, data infrastructure, and site reliability engineering, you will lead the creation of a modern Iceberg-first lakehouse architecture that supports Retrieval-Augmented Generation (RAG), knowledge graphs, vector databases, and agentic AI pipelines. Delivering highly reliable AI infrastructure Build infrastructure capable of supporting sub-second semantic search and large-scale AI pipelines, ensuring enterprise AI systems can access data quickly and efficiently. Implement and optimize Apache Iceberg infrastructure to maintain strong data integrity, consistent metadata management, and scalable lakehouse operations. Provide architectural guidance, reliability patterns, and self-service infrastructure that enable data engineers to deploy and scale pipelines with confidence. Apply now and help change how the world transforms complex data landscapes into actionable insights and turns complex data challenges into new opportunities! Required Experience: 8+ years leading SRE or infrastructure architecture in multi-cloud environments. Infrastructure Expertise: Deep expertise in Kubernetes (K8s) scaling for data workloads, Terraform or Pulumi for IaC, and modern observability stacks (e.g., OpenTelemetry). Lakehouse Experience: Proven record of managing Apache Iceberg at scale, including metadata management, partitioning strategies, and cross-engine consistency. Influence Skills: Strong ability to translate strategic vision into technical guardrails and mentor engineering teams on reliability best practices. Language: Expert-level English (Native or Professional) for global collaboration across time zones. . MCP Experience: Experience with the Model Context Protocol (MCP), including hosting secure, scalable MCP servers and managing transport layers for AI systems. Automation Focus: Background in software engineering with a focus on building automation-first workflows and reducing MTTR. Reporting Line and Collaboration