Architect, Data & Analytics Engineering

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.

Do you have experience in Solution architecture design?, Do you have a Master’s degree?, * 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.

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.