Architect, Data & Analytics Engineering

Job Summary:

Build a Bigger, Better, Bolder Future:
Imagine working for a company that measures its success based off the growth of its colleagues, a company that invests in its future by investing in you. Little Caesars is a company where our colleagues make an impact.
Your Mission:

Little Caesars is seeking a forward-thinking Data & Analytics Architect to define and lead the evolution of our enterprise Data & AI Platform. This role sits at the intersection of business strategy and technology, responsible for enabling scalable, governed, and AI-ready data capabilities across the enterprise. 

You will architect a modern, cloud-based data platform, establish data-as-a-product practices, and enable self-service analytics and AI/ML use cases for both internal stakeholders and franchise partners. This role goes beyond traditional data architecture, focusing on building a platform that powers real-time insights, advanced analytics, and next-generation AI experiences.

What You Will Do:
 

Platform & Architecture Leadership 

• Define and evolve the enterprise Data & AI Platform architecture, spanning ingestion, transformation, storage, semantic modeling, and consumption layers. 
• Establish and scale Lakehouse architecture patterns (e.g., medallion, domain-oriented design). 
• Architect for AI/ML readiness, ensuring high-quality, well-governed data pipelines that support predictive analytics and generative AI use cases. 
• Design for real-time and event-driven data processing to support operational decision-making. 
• Be an evangelist for Dimensional Modeling best practices, ensuring assets in the consumption layer are intuitive, performant, at the appropriate grain, and scalable.  

Data Products & Domain Ownership 

• Lead the adoption of a data product operating model, enabling teams to own, publish, and manage trusted datasets. 
• Partner with business domains (e.g., operations, finance, franchisees) to define domain-driven data models and reusable data assets. 
• Establish standards for data discoverability, documentation, and usability across the organization. 

Semantic Layer & Self-Service Analytics 

• Define and implement a scalable semantic / metrics layer to ensure consistent business definitions across BI, analytics, and AI use cases. 
• Enable self-service analytics by delivering curated, trusted datasets and scalable access patterns. 
• Partner with BI and analytics teams to optimize data consumption experiences across tools and platforms. 

Data Governance, Quality & Trust 

• Establish and mature enterprise data governance frameworks, including data quality, lineage, cataloging, and stewardship. 
• Implement proactive data observability and monitoring to ensure reliability and trust in data products. 
• Design solutions with security standards at the forefront (e.g. principle of least privilege) to ensure data access reflects user needs. 
• Lead root cause analysis and resolution of data quality and integrity issues. 

Engineering Excellence & Scalability 

• Define best practices for data pipeline development, including CI/CD, automated testing, and deployment. 
• Architect scalable batch and streaming data pipelines. 
• Optimize platform performance, reliability, and cloud cost efficiency. 
• Define standards for data sharing, including APIs, external data products, and partner integrations. 

Innovation & Technology Strategy 

• Stay ahead of emerging trends in data, analytics, and AI, including GenAI and LLM-powered applications. 
• Lead proof-of-concepts and technology evaluations, making recommendations on tools and platforms. 
• Play a key role in vendor/platform selection and ecosystem strategy. 
• Develop, maintain, and document customer data management processes and strategies, models and designs. 

Leadership & Influence 

• Act as a trusted advisor to technology and business leadership on data strategy and architecture. 
• Communicate complex technical concepts clearly to non-technical stakeholders. 
• Lead cross-functional initiatives and influence teams without direct authority. 
• Champion a culture of data-driven decision-making and continuous improvement. 

Who You Are:

• Bachelor’s degree in computer science, data analytics, data science or related field. Relevant experience may be considered in lieu of formal degree. 
• 8+ years of experience in data architecture, data engineering, or analytics engineering, with increasing scope and ownership. 
• Proven experience designing and implementing modern cloud-based data platforms (AWS, Azure, or Google Cloud). 
• Deep expertise in data modeling (dimensional, normalized, and domain-driven design). 
• Strong experience with SQL and modern data transformation frameworks (e.g., dbt or equivalent). 
• Hands-on experience with Lakehouse technologies (e.g., Databricks, Snowflake, BigQuery). 
• Experience implementing semantic/metrics layers and enabling consistent business definitions. 
• Strong understanding of data governance, cataloging, lineage, and data quality frameworks. 
• Experience with data observability and monitoring tools. 

What Will Make You Stand Out:

• Masters degree in information technology, computer science, data analytics, data science or related field. 
• Familiarity with AI/ML data requirements, feature engineering, and enabling data for GenAI/LLM use cases. 
• Proven ability to translate business needs into scalable, reusable, and high-impact data solutions. 
• Strong communication and leadership skills, with experience influencing senior stakeholders. 
• Curious, innovative, and passionate about building next-generation data and AI capabilities.

Disclaimer:

The above is intended to describe the general content of and requirements for the performance of this job.  It is not to be construed as an exhaustive statement of duties, responsibilities, or requirements.

All items listed above are illustrative and not comprehensive.  They are not contractual in nature and are subject to change at the discretion of Little Caesars Enterprises Inc.      

Little Caesar Enterprises, Inc. is an Equal Employment Opportunity employer. All qualified applicants will receive consideration for employment without regards to that individual’s race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender identity, age, physical or mental disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law.                                   
The Company will strive to provide reasonable accommodations to permit qualified applicants who have a need for an accommodation to participate in the hiring process (e.g., accommodations for a job interview) if so requested.  
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