Principal Engineer – Public Cloud Data

Jobtailor

Arizona

On-site

USD 150,000 - 185,000

Full time

3 days ago

Be an early applicant

Get more replies from employers

Send a job-specific resume in minutes.

Job summary

Jobtailor is seeking a Senior Enterprise Architect to define target-state architecture for cloud-native data, analytics, and AI/Agentic AI platforms. You will establish standards, reusable patterns, and governance across the enterprise, while modernizing legacy data platforms into scalable cloud-native ecosystems.

You will lead technology evaluations, architect enterprise lakehouse and data mesh solutions, and drive adoption of cutting-edge cloud capabilities with a focus on governance,

Qualifications

Advanced degree in Computer Science, Engineering, Data Science, AI, or related field.
Industry certifications in public cloud, data engineering, AI/ML, or security.
Experience in regulated industries such as financial services, healthcare, or insurance.
7+ years designing enterprise-scale data and analytics platforms.
7+ years of engineering experience or equivalent demonstrated through work experience.

Responsibilities

Define target-state architecture for cloud-native data, analytics, AI/ML, and Agentic AI platforms (enterprise scope).
Establish engineering standards, reference architectures, reusable patterns, and governance.
Drive modernization of legacy data platforms into scalable cloud-native ecosystems.
Lead evaluations and adoption of emerging public cloud capabilities.
Architect and scale lakehouse, data mesh, streaming, real-time analytics platforms.

Skills

Cloud-Native Data Architecture

AI/ML Solutions Development

Data Governance and Quality

Infrastructure as Code

Public Cloud Platforms

Education

Advanced degree in Computer Science/Engineering/Data Science/AI

Tools

Google Cloud Platform

Microsoft Azure

Amazon Web Services

BigQuery

Snowflake

Databricks

Starburst

Job description

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 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

Requirements

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
Experience with Microsoft Azure and/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
Advanced degree in Computer Science, Engineering, Data Science, AI, or related field
Industry certifications in public cloud, data engineering, AI/ML, or security
Experience in highly regulated industries such as financial services, healthcare, or insurance
This position is not eligible for visa sponsorship

Core Competencies

Demonstrates expertise in architecting cloud-native data and analytics platforms, with a strong focus on AI/ML solutions and data governance. Proven ability to lead enterprise-wide cloud transformation initiatives while ensuring compliance and security standards are met.

Highest-signal resume keywords