Little Caesars

Architect,Data&AnalyticsEngineering

Detroit, Michigan, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Architect, Data & Analytics Engineering at Little Caesars. Skills: Data & AI Platform architecture, Cloud-based data platforms, Lakehouse architecture patterns, Data product operating model, Semantic / metrics layer, Data governance frameworks, Scalable batch and streaming data pipelines. Define and lead the evolution of the enterprise Data & AI Platform.. Architect a modern, cloud-based data platform.”

What You'll Achieve.

Enabling scalable, governed, and AI-ready data capabilities across the enterprise.; Building a platform that powers real-time insights, advanced analytics, and next-generation AI experiences.; Ensuring assets in the consumption layer are intuitive, performant, at the appropriate grain, and scalable.; Enabling teams to own, publish, and manage trusted datasets.; Ensuring consistent business definitions across BI, analytics, and AI use cases.; Delivering curated, trusted datasets and scalable access patterns.; Ensuring reliability and trust in data products.; Ensuring data access reflects user needs.; Optimizing platform performance, reliability, and cloud cost efficiency.

Industry & Context.

Problems you'll solve

Lead root cause analysis and resolution of data quality and integrity issues.

What They're Looking For.

Must Have

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)., 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., understanding of data governance, cataloging, lineage, and data quality frameworks., Experience with data observability and monitoring tools.

Nice to Have

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., communication and leadership skills, with experience influencing senior stakeholders., Curious, innovative, and passionate about building next-generation data and AI capabilities.

What You'll Do.

Define and lead the evolution of the enterprise Data & AI Platform.

cloud-based data platform.

Establish data-as-a-product practices.

Enable self-service analytics and AI/ML use cases.

Define and evolve the enterprise Data & AI Platform architecture

and consumption layers.

Establish and scale Lakehouse architecture patterns.

Architect for AI/ML readiness.

Design for real-time and event-driven data processing.

Evangelize Dimensional Modeling best practices.

Lead the adoption of a data product operating model.

Partner with business domains to define domain-driven data models and reusable data assets.

Establish standards for data discoverability

Define and implement a scalable semantic / metrics layer.

Enable self-service analytics.

Partner with BI and analytics teams to optimize data consumption experiences.

Establish and mature enterprise data governance frameworks.

Implement proactive data observability and monitoring.

Design solutions with security standards at the forefront.

Lead root cause analysis and resolution of data quality and integrity issues.

Define best practices for data pipeline development.

Architect scalable batch and streaming data pipelines.

Optimize platform performance

and cloud cost efficiency.

Define standards for data sharing.

Stay ahead of emerging trends in data

Lead proof-of-concepts and technology evaluations.

Play a key role in vendor/platform selection and ecosystem strategy.

and document customer data management processes and strategies

How You'll Work.

Team & Collaboration

Partner with business domains (e.g., operations, finance, franchisees) to define domain-driven data models and reusable data assets.; Partner with BI and analytics teams to optimize data consumption experiences across tools and platforms.; Lead cross-functional initiatives and influence teams without direct authority.

Communication Scope

Communicate complex technical concepts clearly to non-technical stakeholders.

Full Job Description

**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 asse

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