Principal Engineer – Public Cloud Data

Wells Fargo

. Define the target-state architecture for cloud-native data, analytics, AI/ML, and Agentic AI platforms .

Posted 10/16/2026full-timeUnited StatesLead💰 $159,000 - $254,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting cloud-native data ecosystems, AI/ML solutions, and data governance frameworks while ensuring compliance with regulatory standards. Proven ability to lead enterprise-wide cloud transformation initiatives and implement Infrastructure as Code practices.

Highest-signal resume keywords

Cloud-Native Data ArchitectureAI/ML Solutions DeliveryData Governance and QualityPublic Cloud Platforms ExpertiseInfrastructure as Code

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Applicant Tracking System Keywords

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Hard Skills

Data Lakehouse ArchitectureStreaming and Event-Driven ArchitecturesKubernetes and Container PlatformsMLOps FrameworksLarge Language Models (LLMs)Retrieval Augmented Generation (RAG)Agentic AI ArchitecturesMetadata ManagementData TransformationTechnical Leadership

Soft Skills

CollaborationStrategic ThinkingProblem SolvingCommunicationLeadership

Tools & Technologies

Google Cloud PlatformMicrosoft AzureAmazon Web ServicesBigQuerySnowflakeDatabricksStarburstKubernetesDevOps AutomationAI Governance Controls

Certifications & Qualifications

Public Cloud CertificationsData Engineering CertificationsAI/ML CertificationsSecurity Certifications

Industry Keywords

Financial ServicesHealthcareInsuranceRegulatory ComplianceEnterprise Architecture

Tech Stack

Tools & technologies

AWSAzureBigQueryCloudCyber SecurityGoogle Cloud PlatformKubernetes

About the role

Key responsibilities & impact

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 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, and 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, 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 adoption
Design high-performance, secure, and cost-efficient cloud data ecosystems supporting regulatory and business requirements

Requirements

What you’ll need

7+ years of Engineering experience, or equivalent demonstrated through 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
Deep expertise in one or more public cloud platforms; Google Cloud Platform preferred, Microsoft Azure, or Amazon Web Services
Strong experience with data lakehouse architectures
Experience with BigQuery, Snowflake, Databricks, Starburst, or equivalent platforms
Experience with streaming and event-driven architectures
Experience with data governance, metadata, lineage, and catalog solutions
Experience with Kubernetes and container platforms
Experience with Infrastructure as Code and DevOps automation
Experience designing enterprise AI platforms and MLOps frameworks
Experience with Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Agentic AI architectures, multi-agent systems, vector databases, model evaluation and monitoring, and MCP ecosystems
Experience implementing production-grade AI governance and controls
Experience in highly regulated industries such as financial services, healthcare, or insurance
Advanced degree in Computer Science, Engineering, Data Science, AI, or related field preferred
Industry certifications in public cloud, data engineering, AI/ML, or security preferred
Contributions to industry standards, patents, open-source projects, or published technical thought leadership preferred
This position is not eligible for visa sponsorship

Benefits

Comp & perks

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement
Incentive opportunities may be available