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Principal Enterprise Architect - Data & AI

Gap Inc.

United States

Remote

USD 130,000 - 180,000

Full time

Yesterday
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Job summary

A leading company in the retail sector is seeking a Principal Enterprise Architect – Data & AI to drive architectural strategy and implementation of data-driven AI solutions. This role involves collaboration across multiple teams to ensure technology aligns with business goals while mentoring and establishing standards within the data and AI domain.

Qualifications

  • Minimum of 7 years of professional experience in technology.
  • At least 3 years in data architecture and AI solution architect role.
  • Strong expertise in cloud platforms, preferably Azure and GCP.

Responsibilities

  • Develop end-to-end solution architectures for data-driven and AI-focused applications.
  • Lead architecture design efforts across data pipelines and AI applications.
  • Provide technical leadership and mentoring in data engineering and AI best practices.

Skills

Cloud platforms
Data architecture
AI solutions
Data governance
Programming
Stakeholder management

Education

Bachelor's or Master’s degree in Computer Science, Data Science, Engineering

Tools

Azure Data Factory
Confluent Kafka
Spark
Databricks
BigQuery
Vertex AI
TensorFlow
PyTorch
Spark ML
Azure ML

Job description

About the RoleAs Principal Enterprise Architect – Data & AI, you will lead the architectural strategy, solution design, and roadmap execution across our enterprise Data & AI Domain. As a key member of this team, you will design, develop, and guide the implementation of cutting-edge data-driven AI solutions that power many of our initiatives that have touch points with Product-to-Market, Omni-channel and Loyalty programs. We welcome passionate individuals ready to drive strategic impact and innovation through intelligent, data-driven solutions.What You'll Do

  • Develop end-to-end solution architectures for data-driven and AI-focused applications, ensuring alignment with business objectives and technology strategy.

  • Lead architecture design efforts across data pipelines, machine learning models, AI applications, and analytics platforms in our Gap Data Platform area.

  • Collaborate closely with business partners, product managers, data scientists, software engineers, and the broader Global Technology Solutions teams in vetting solution design and delivering business value.

  • Provide technical leadership and mentoring in data engineering and AI best practices.

  • Evaluate and recommend emerging data technologies, AI techniques, and cloud services to enhance business capabilities.

  • Ensure the scalability, performance, and security of data and AI architectures.

  • Establish and maintain architectural standards, including patterns and guidelines for data and AI projects.

  • Create architecture artifacts(concept, system, data architecture) for data and AI projects/initiatives.

  • Create and oversee architecture center of excellence for data and AI area to coach and mentor resources working in this area.

Who You Are
  • Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, or related discipline.

  • Minimum of 7 years of professional experience in technology, including at least 3 years in a data architecture and AI solution architect role.

  • Strong expertise in cloud platforms, preferably Azure and GCP, and associated data and AI services.

  • Proven experience in architecting and deploying scalable data solutions, including data lakes, warehouses, and streaming platforms.

  • Working knowledge of tools/technologies like Azure Data Factory, Confluent Kafka, Spark, Databricks, BigQuery and Vertex AI.

  • Deep understanding of AI/ML frameworks and tools such as TensorFlow, PyTorch, Spark ML, or Azure ML.

  • Proficiency with programming languages like Python, Java, or Scala.

  • Solid understanding of data governance, security, privacy, and compliance standards.

  • Exceptional communication, presentation, and stakeholder management skills.

  • Experience working in agile project environments.

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