Principal Data Platform Engineer
4 hours ago
About the role:
ZoomInfo is looking for a Principal Data Platform Infrastructure Engineer to design and scale our next-generation Self Service AI-ready enterprise data platform. This role is at the intersection of data infrastructure and AI, powering LLM chatbots, intelligent agents, and advanced analytics at enterprise scale. You'll drive architecture across the data platform, semantic layer, Model Context Protocol (MCP) services, and governance automation, ensuring consistent, reliable, and high-quality outcomes.
What you'll do:
- Lead the architecture of an AI-first enterprise data platform
- Build and scale MCP-driven tooling, context fabric, and semantic contracts
- Automate governance, data quality, lineage, and policy-as-code frameworks
- Implement PII classification/redaction and multi-tenant context scoping
- Ensure reliability, observability, performance, and cost efficiency across the platform
- Partner with Data Engineering, Analytics, and ML/AI teams on access patterns and evaluation standards
- Drive proof-of-concepts (POCs) and platform innovation initiatives
- Establish best practices in Infrastructure-as-Code, CI/CD, and automated policy enforcement
Basic qualifications:
- 7+ years designing and building large-scale data platforms and distributed cloud systems
- 1+ year of experience with LLMs, RAG, search, or information retrieval systems
- Bachelor's degree in Computer Science, Engineering, or equivalent experience
- Advanced SQL skills and warehouse expertise (Snowflake, BigQuery, Redshift)
- Strong programming skills in Python; experience with microservices and data services
- Workflow orchestration (Airflow) and modeling (dbt) system setup and abstraction experience
- Batch/streaming systems design expertise such as Kafka, Spark, Beam, Dataflow, EMR
- Proven background in metadata systems & governance: data contracts, catalogs, OpenLineage
- Infrastructure experience: Kubernetes, serverless (Lambda/Cloud Functions), Terraform, CI/CD (GitHub Actions / Jenkins)
- Experience in data security & privacy: IAM, secrets management, encryption, tenant isolation
- Understanding of MCP tool servers/clients, capability registries, and observability patterns
- Knowledge of Lakehouse formats such as Delta Lake, Iceberg, Hudi.
- Familiarity with FinOps for AI: cost controls, token budgeting, caching strategies
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