Principal Engineer - Public Cloud Data

About this role: The Principal Engineer for Public Cloud Data, Analytics & Agentic AI Platform is the senior-most technical leader responsible for defining and driving the strategic architecture, engineering standards, and innovation roadmap for enterprise-scale data, analytics, and Agentic AI capabilities on public cloud platforms. This role serves as the technical authority for modern data platforms, AI-native architectures, and autonomous agent solutions that enable self-service analytics, intelligent automation, real-time decisioning, and enterprise-scale data products. The Principal Engineer partners with engineering, architecture, cybersecurity, risk, compliance, product, and business leaders to accelerate cloud transformation while maintaining security, governance, resilience, and regulatory compliance. In this role, you will: Define the target-state architecture for cloud-native data, analytics, AI/ML, and Agentic AI platforms Establish engineering standards, reference architectures, reusable patterns, and technical governance across the enterprise Drive modernization of legacy data platforms into scalable cloud-native ecosystems Lead technology evaluations and strategic adoption of emerging public cloud capabilities Architect and scale enterprise lakehouse, data mesh, streaming, and real-time analytics platforms Define standards for data ingestion, transformation, governance, metadata management, lineage, and data quality Enable self-service data products and analytics capabilities across business lines Lead the development of Agentic AI solutions that automate engineering, operations, governance, and analytics workflows Define enterprise frameworks for AI agents, orchestration, reasoning engines, MCP-based integrations, and human-in-the-loop controls Architect AI-enabled automation for: Data onboarding Pipeline generation Metadata enrichment Policy enforcement Data quality validation Incident remediation Operational intelligence Establish standards for responsible AI, explainability, model governance, and auditability Provide technical leadership across public cloud services including compute, storage, networking, security, AI, analytics, and DevOps ecosystems Drive platform reliability, scalability, resiliency, observability, disaster recovery, and operational excellence Partner with engineering teams to implement Infrastructure as Code (IaC), platform automation, and self-service capabilities Establish SLOs, reliability metrics, and engineering KPIs Partner with Cyber Security, IAM, Risk, Audit, and Regulatory Compliance teams Ensure cloud platforms meet enterprise security, governance, privacy, and regulatory standards Architect secure-by-design and compliance-by-design platform capabilities Drive implementation of AI governance controls for enterprise-scale Agentic AI adoptio Design high-performance, secure, and cost-efficient cloud data ecosystems supporting regulatory and business requirements Required Qualifications: 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 7+ years designing enterprise-scale data and analytics platforms 5+ years delivering AI/ML, Generative AI, or Agentic AI solutions in complex enterprise environments Proven experience leading enterprise-wide cloud transformation initiatives Desired Qualifications: Deep expertise in one or more public cloud platforms: Google Cloud Platform (preferred) Microsoft Azure Amazon Web Services Strong experience with: Data Lakehouse architectures BigQuery, Snowflake, Databricks, Starburst, or equivalent platforms Streaming and event-driven architectures Data governance, metadata, lineage, and catalog solutions Kubernetes and container platforms Infrastructure as Code and DevOps automation AI & Agentic AI Expertise Experience designing enterprise AI platforms and MLOps frameworks. Large Language Models (LLMs) Retrieval Augmented