Director, Data Platform Engineering

The Director Data & AI - Data Engineering & Platforms is responsible for defining refining and executing Dominos enterprise data strategy data platform roadmap and data engineering operating model. This leader oversees enterprise data platforms data engineering enterprise data products data quality engineering data base administration and data operations capabilities that enable trusted scalable and secure data across the organization.

This role leads the teams responsible for designing building operating and continuously improving the data foundations that power analytics reporting operational systems predictive AI and generative AI solutions. Working closely with business and technology stakeholders the Director ensures Dominos data assets are reliable discoverable and ready to support growing enterprise demand for data-driven decision making.

Responsibilities

Strategy & Leadership

• Define and evolve the enterprise data platform engineering and operations strategy.
• Develop and manage a multi-year roadmap aligned to business priorities and technology modernization goals.
• Drive a data-as-a-product culture focused on trusted reusable and business-aligned data assets.
• Serve as a trusted advisor to 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.

Data Engineering & Platforms

• Lead the strategy architecture and operation of Dominos 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 CI/CD automation and observability.
• Evaluate and adopt emerging technologies that improve engineering productivity platform capabilities and operational effectiveness.

Enterprise Data Products

• 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 success through adoption quality reliability and business impact.

Data Foundations for Analytics & AI

• Ensure enterprise data platforms and data products provide trusted data foundations for analytics predictive AI and generative AI solutions.
• Develop and operate feature-serving capabilities that support machine learning and predictive modeling workloads.
• Develop and operate context-serving capabilities that support enterprise knowledge retrieval and generative AI 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 that improve trust in downstream analytics and AI solutions.

Data Quality & Operations

• 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 KPIs 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.

People Leadership

• 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 top 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.

Qualifications :

• Bachelors degree in Computer Science Information Technology Engineering Data Science or related field.
• 10 years of experience in data engineering data platforms cloud data technologies or enterprise data management.
• 5 years of leadership experience managing engineering platform or technology teams.
• Proven experience building and operating enterprise-scale data platforms and data products.
• Strong expertise with cloud-based data platforms modern data architecture patterns and large-scale distributed data processing.
• Experience leading data quality operational support and platform reliability initiatives.
• Strong communication and stakeholder management skills with the ability to influence across technical and business audiences.
• Demonstrated ability to translate business objectives into scalable technology solutions and roadmaps.

Preferred 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.

Additional Information :

Benefits:

• Paid Holidays and Vacation 
• Medical Dental & Vision benefits that start on the first day of employment
• No-cost mental health support for employee and dependents
• Childcare tuition discounts
• No-cost fitness nutrition and wellness programs 
• Fertility benefits
• Adoption assistance
• 401k matching contributions 
• 15% off the purchase price of stock 
• Company bonus 
   

All your information will be kept confidential according to EEO guidelines.

Remote Work :

No

Employment Type :

Full-time