Principal Data Platform Infrastructure Engineer

Job Title:

Principal Data Platform Infrastructure Engineer

Location: Raanana, Center District, Israel

Type: Full-time

Work Arrangement: On-site or hybrid (not explicitly stated, but likely hybrid)

About the Role

ZoomInfo is seeking a Principal Engineer to design and scale an AI-first, self-service enterprise data platform. This role sits at the intersection of data infrastructure and AI, directly powering solutions like LLM chatbots, intelligent agents, and enterprise analytics.

You’ll define and own architecture across:

• The data platform
• Semantic layers
• Model Context Protocol (MCP) services
• Governance and policy automation

This is a hands-on, high-impact leadership role partnering with ML, analytics, and data engineering teams across the business.

Key Responsibilities

• Architect and build an AI-ready, enterprise-scale data platform
• Lead development of MCP tooling, context fabric, semantic contracts
• Automate data governance, lineage, quality, and policy-as-code
• Build PII classification, redaction, and multi-tenant isolation
• Ensure platform reliability, observability, and cost optimization
• Collaborate with internal teams (AI, ML, analytics, data engineering)
• Lead proof-of-concepts (PoCs) and innovation efforts
• Drive best practices in Infrastructure-as-Code (IaC) and CI/CD

Basic Qualifications

• 12+ years building large-scale cloud data platforms
• 1+ year hands-on experience with LLMs, RAG, IR systems
• Bachelor’s in Computer Science, Engineering, or related field
• Expert in SQL and data warehouses: Snowflake, BigQuery, Redshift
• Strong Python skills; experience in microservices and data services
• Experience with:
• Workflow orchestration: Airflow, dbt
• Streaming/batch systems: Kafka, Spark, Beam, Dataflow
• Metadata & governance: data contracts, catalogs, OpenLineage
• Cloud infrastructure: Kubernetes, serverless (Lambda), Terraform, CI/CD
• Security: IAM, encryption, secrets management, tenant isolation
• Familiar with:
• MCP tool servers/clients, capability registries
• Lakehouse formats: Delta Lake, Iceberg, Hudi
• FinOps for AI (cost optimization, token budgets, caching)

Why This Role Stands Out

• Shapes the future of data architecture powering real-time AI
• Key to enabling LLM-based applications at enterprise scale
• High autonomy and direct influence on strategic platform design
• Collaboration with global teams across AI, ML, analytics, infra