Principal Engineer - Data Platforms (On prem, cloud, AI/ML, Infra)

Target • Sunnyvale, CA

1d • $163,000 - $353,000 • Hybrid

About The Position

The Principal Engineer – Data Platform is responsible for shaping the technical direction of Target’s enterprise data platform. This role operates with broad scope and high impact across data platform engineering, AI/ML infrastructure, and modern data consumption experiences. You will be a hands-on engineer who designs, builds, and evolves scalable platform capabilities while influencing architectural decisions across teams. Your work will span large-scale data processing, GPU-enabled AI/ML infrastructure on Kubernetes, and emerging GenAI and agentic AI approaches to data access, automation, and insight generation. Success is defined by technical excellence, system-level thinking, and the ability to turn ambiguity into durable, extensible platform solutions. The Enterprise Data Platform Engineering team builds the foundational capabilities that power data engineering, data analytics, AI/ML, and operational use cases across Target. We are evolving toward a highly automated, self-service, and AI-enabled platform that supports enterprise scale and rapid innovation. As a Principal Engineer, you will… Provide technical leadership and design: Act as a technical authority for the data platform, shaping scalable, secure, and reliable architectures and influencing design decisions across multiple teams. Drive platform scalability and reliability: Design and operate large-scale distributed data systems with a focus on performance, cost efficiency, observability, and operational automation across hybrid (cloud and on-prem) infrastructure. Lead AI/ML and GPU infrastructure: Architect and evolve Kubernetes-based AI/ML platforms, including GPU-enabled workloads, and ensure strong integration with the broader data and AI / ML Platform. Advance agentic AI innovation: Explore and productionize GenAI capabilities for data-centric use cases such as SQL generation, data discovery, troubleshooting, and platform automation, with appropriate guardrails. Shape next-generation data consumption: Define modern data access patterns including semantic modeling, visualization, APIs, and seamless integration with data consumers. Lead through hands-on engineering and influence: Write production-quality code and infrastructure, mentor through design and review, and partner closely with product and engineering stakeholders. Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

Requirements

• 4-year degree in Computer Science, Engineering, or equivalent experience
• 10+ years of experience building large-scale software, data, or distributed systems
• Deep expertise in distributed data platforms and modern data architectures
• Strong hands-on experience operating data platforms in both cloud and on-prem environments, with a focus on reliability, scalability, and operational excellence
• Proven experience with query engines and query optimization, including performance tuning, cost optimization, and scaling analytical workloads
• Strong background in cloud-native architectures and Kubernetes-based infrastructure
• Hands-on experience with AI/ML infrastructure, including GPU-enabled workloads
• Experience designing high-performing APIs, platform abstractions and self-service data capabilities
• Proven ability to influence technical direction without direct authority
• Passion for emerging technologies and how they are applied to solve real-world data problems
• Strong communication skills and a systems-thinking mindset
• Team player who understands concepts of teamwork and team effectiveness
• Has excellent verbal, written, and presentation communication skills to convey complex technical solutions clearly to an organization

Responsibilities

• Provide technical leadership and design: Act as a technical authority for the data platform, shaping scalable, secure, and reliable architectures and influencing design decisions across multiple teams.
• Drive platform scalability and reliability: Design and operate large-scale distributed data systems with a focus on performance, cost efficiency, observability, and operational automation across hybrid (cloud and on-prem) infrastructure.
• Lead AI/ML and GPU infrastructure: Architect and evolve Kubernetes-based AI/ML platforms, including GPU-enabled workloads, and ensure strong integration with the broader data and AI / ML Platform.
• Advance agentic AI innovation: Explore and productionize GenAI capabilities for data-centric use cases such as SQL generation, data discovery, troubleshooting, and platform automation, with appropriate guardrails.
• Shape next-generation data consumption: Define modern data access patterns including semantic modeling, visualization, APIs, and seamless integration with data consumers.
• Lead through hands-on engineering and influence: Write production-quality code and infrastructure, mentor through design and review, and partner closely with product and engineering stakeholders.

Benefits

• Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves.
• Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation.
• Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Number of Employees: 5,001-10,000 employees