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Domino's

Global pizza delivery and franchise network

Director Data Platform Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeAnn Arbor, MI, USAIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field is required.
  • At least 10 years of experience in data engineering, data platforms, cloud data technologies, or enterprise data management is required.
  • At least 5 years of leadership experience managing engineering, platform, or technology teams is required.
  • Experience building and operating enterprise-scale data platforms and data products is required.
  • Expertise with cloud-based data platforms, modern data architecture patterns, and large-scale distributed data processing is required.
  • Experience leading data quality, operational support, and platform reliability initiatives is required.
  • The candidate must be able to communicate with and influence technical and business audiences and manage stakeholders.
  • The candidate must be able to translate business objectives into scalable technology solutions and roadmaps.

Responsibilities

  • Define and evolve enterprise data platform, engineering, and operations strategy.
  • Develop and manage a multi-year roadmap aligned with business priorities and technology modernization goals.
  • Drive a data-as-a-product culture focused on trusted, reusable, and business-aligned data assets.
  • Advise senior business and technology leaders on data platform investments and capabilities.
  • Establish goals, operating metrics, and performance measures that drive continuous improvement and business value.
  • Lead the strategy, architecture, and operation of enterprise data platforms and engineering capabilities.
  • Establish standards for reliability, scalability, performance, security, availability, and cost optimization.
  • Lead the design and delivery of scalable batch, streaming, and real-time data solutions.
  • Drive engineering best practices across data modeling, software development, testing, continuous integration and continuous delivery, automation, and observability.
  • Evaluate and adopt emerging technologies to improve engineering productivity, platform capabilities, and operational effectiveness.
  • Own the enterprise data product strategy and roadmap for foundational data assets consumed across the organization.
  • Establish standards for data product ownership, lifecycle management, reliability, discoverability, and operational support.
  • Partner with analytics, application, and business teams to develop reusable and scalable enterprise data products.
  • Enable self-service analytics and data consumption through consistent, trusted, and well-documented data assets.
  • Measure data product success through adoption, quality, reliability, and business impact.
  • Ensure enterprise data platforms and data products provide trusted data foundations for analytics, predictive artificial intelligence, and generative artificial intelligence solutions.
  • Develop and operate feature-serving capabilities for machine learning and predictive modeling workloads.
  • Develop and operate context-serving capabilities for enterprise knowledge retrieval and generative artificial intelligence experiences.
  • Partner with Data Science, AI Engineering, Architecture, and Analytics teams to support evolving data consumption patterns.
  • Drive investments in metadata, lineage, observability, and data quality to improve trust in downstream analytics and AI solutions.
  • Lead the Data Quality Engineering and Data Operations functions.
  • Establish enterprise standards for monitoring, validation, reconciliation, issue management, and operational support.
  • Drive operational excellence through incident management, root cause analysis, automation, and continuous improvement.
  • Define and monitor service levels, operational key performance indicators, and platform health metrics.
  • Partner with business governance, security, compliance, and analytics stakeholders to ensure platforms support approved enterprise policies, business definitions, and regulatory requirements.
  • Build, lead, and develop a high-performing organization of managers, engineers, and technical specialists.
  • Foster a culture of ownership, accountability, collaboration, and technical excellence.
  • Recruit, retain, and develop talent while creating clear career growth opportunities.
  • Manage team budgets, resource allocation, vendor relationships, and strategic investments.
  • Promote continuous learning and adoption of modern engineering practices across the organization.

Desired Qualifications

  • Experience leading enterprise data modernization or cloud transformation initiatives.
  • Experience enabling advanced analytics, feature serving for predictive AI, and context serving for generative AI solutions.
  • Familiarity with modern lakehouse architectures, data product operating models, and DataOps practices.
  • Cloud and data platform certifications.
  • Experience in retail, restaurant, digital commerce, or other high-volume consumer-focused industries.

About the Company

Domino's

Global pizza delivery and franchise network

Domino’s delivers pizza and related items worldwide through a network of franchise stores. Customers place orders online, via app, or in-store; store teams prepare the pizzas and drivers deliver them or customers pick up, with a focus on speed and consistency. Its global franchise system provides broad reach, standardized service, and a strong brand, along with community involvement. Its goal is to be the leading pizza company by delivering great-tasting pizzas quickly and expanding its global footprint while supporting franchisees and communities.

Company size
10,001+
Company stage
IPO
Headquarters
United Kingdom
Founded
1960

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