Data Architect, Enterprise Data Platform

Posted 5 Days Ago
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2 Locations
In-Office
Senior level
Food
The Role
Designs and maintains enterprise dimensional data models, semantic layers, metadata structures, and analytics architecture. The role applies star schema standards, validates model quality, supports governance and lineage, and aligns source, transformed, and published data layers. It partners with data engineers, business stakeholders, governance teams, and analytics users to improve scalability, performance, consistency, discoverability, and trusted reporting across the enterprise.
Summary Generated by Built In

Your Opportunity as the Data Architect, Enterprise Data Platform

The Data Architect is responsible for designing and maintaining enterprise data models that support analytics, reporting, and data-driven decision making. This role ensures that data structures are scalable, consistent, and aligned to business needs, while supporting efficient data consumption across the organization.  The Data Architect contributes to enterprise analytics data governance and modeling standards by defining data structures, validating implementations, improving model quality and consistency, and working across data domains to ensure alignment between source data, engineered data layers, and published analytics assets.

This role applies and enforces dimensional modeling best practices using star schema design, including fact and dimension tables, conformed dimensions, and standardized metrics. Data models are designed to support a unified semantic layer and enable accurate, consistent reporting across tools such as Tableau.

Work Arrangements: Hybrid - onsite a minimum of 9 days a month primarily during core weeks as determined by the Company; maybe more as business need requires

In this role you will:

  • Data Modeling & Design

    • Design, develop, and maintain dimensional data models using star schema methodology, including defining fact tables, dimension tables, grain, and relationships that support enterprise analytics and reporting.

    • Ensure models are optimized for performance, scalability, and usability.

    • Create and maintain conceptual, logical, and physical data models using appropriate modeling tools.

    • Analyze and profile new data sources to understand structure, quality, relationships, and business context, informing appropriate modeling and architecture decisions.

  • Model Quality & Standards

    • Apply enterprise data modeling standards and best practices across all solutions.

    • Validate data models for consistency, accuracy, and alignment with business requirements.

    • Identify and resolve issues related to duplication, inconsistency, poor model design, or data quality concerns that impact analytics and reporting.

    • Improve data model usability and clarity for downstream analytics and reporting.

    • Represent the Enterprise Data Platform team in architecture review boards and design reviews, providing guidance on data modeling, semantic consistency, and analytics architecture considerations.

  • Semantic Alignment & Analytics Support

    • Establish and maintain a consistent semantic layer, including standardized metrics, dimensions, and business logic that support trusted analytics and reporting.

    • Align data models with reporting requirements, certified data sources, and enterprise analytics standards.

    • Support analytics teams by providing clear, well-structured, and consumable data models.

  • Data Architecture & Solution Design

    • Develop and guide data architecture decisions related to data structures and design patterns.

    • Collaborate with Data Engineers to ensure data pipeline implementations align with the intent of approved data models, enterprise standards, and architectural best practices while meeting performance and scalability requirements.

    • Partner with Data Owners, domain experts, engineers, and analytics teams to align data models with business processes, priorities, and enterprise standards.

    • Recommend improvements to data design, storage, and structure.

    • Ensure alignment across source, transformed, and published data layers.

  • Governance & Documentation

    • Support metadata, lineage, and documentation standards.

    • Define and document data models, including structure, definitions, and usage guidance.

    • Ensure models align with governance standards for ownership, classification, and compliance.

    • Contribute to improving discoverability and trust in enterprise data.

    • Collaborate with platform, governance, and security teams to ensure data models and architecture designs align with enterprise security, privacy, data classification, and access control standards.

What we are looking for

  • Minimum Requirements:

    • Bachelor’s degree, equivalent experience or specialized training in Information Technology

    • 8+ years of experience in data modeling, data architecture, analytics, or senior data engineering environments

    • Demonstrated ability to collaborate effectively across technical teams, business stakeholders, and data domain partners to drive alignment and adoption

    • Advanced SQL skills and experience working with large datasets

    • Experience designing data models, metadata structures, and semantic foundations that support trusted analytics, reporting, and emerging AI use cases

    • Experience with Databricks, lakehouse architectures, or similar modern cloud data platforms

    • Strong understanding of data structures, relationships, and performance optimization

    • Ability to think critically and conceptually, communicate complex data architecture topics clearly, and adapt recommendations for both technical and nontechnical audiences

  • Additional skills and experience that we think would make someone successful in this role (not required):

    • Experience creating and maintaining conceptual, logical, and physical data models using enterprise modeling tools such as ER/Studio, Erwin, or equivalent platforms

    • Experience leveraging metadata management, data catalog, lineage, and governance capabilities to improve data discoverability, traceability, and trust across enterprise analytics environments, including platforms such as Atlan or similar solutions

    • Experience working across multiple areas of the analytics lifecycle, including data engineering, data modeling, and business intelligence/reporting solutions

    • Familiarity with Python and modern data engineering workflows

    • Familiarity with source control and collaborative development practices (e.g., Git, GitHub, Azure DevOps)

    • Understanding of modern data platform concepts and workflows

    • Understanding of how data architecture, metadata, and governance enable trusted analytics and AI solutions

The Right Place for You 

We are bold, kind, strive to do the right thing, we play to win, and we believe in a strong community that thrives together. Our culture is rooted in our Basic Beliefs, and we believe in supporting every employee by meeting their physical, emotional, and financial needs. 

Stay connected with us on LinkedIn® 

We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, genetic information, age, national origin, disability status or protected veteran status. 

Skills Required

  • Bachelor's degree, equivalent experience, or specialized training in Information Technology
  • 8+ years of experience in data modeling, data architecture, analytics, or senior data engineering environments
  • Ability to collaborate across technical teams, business stakeholders, and data domain partners
  • Advanced SQL skills and experience working with large datasets
  • Experience designing data models, metadata structures, and semantic foundations for analytics, reporting, and emerging AI use cases
  • Experience with Databricks, lakehouse architectures, or similar modern cloud data platforms
  • Strong understanding of data structures, relationships, and performance optimization
  • Ability to communicate complex data architecture topics clearly to technical and nontechnical audiences
  • Experience creating conceptual, logical, and physical data models using ER/Studio, Erwin, or equivalent tools
  • Experience with metadata management, data catalogs, lineage, and governance platforms such as Atlan
  • Experience across data engineering, data modeling, and business intelligence or reporting
  • Familiarity with Python and modern data engineering workflows
  • Familiarity with Git, GitHub, Azure DevOps, or similar collaborative development tools
  • Understanding of modern data platform concepts and workflows
  • Understanding of how data architecture, metadata, and governance support trusted analytics and AI solutions

The J.M. Smucker Co. Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about The J.M. Smucker Co. and has not been reviewed or approved by The J.M. Smucker Co..

  • Retirement Support Retirement programs are described as strong, with a company 401(k) match, immediate vesting in some materials, and access to an Employee Stock Purchase Plan. These elements contribute to a favorable view of total compensation value.
  • Parental & Family Support Paid parental leave for all parents and on-site childcare at key locations signal a family-forward approach. Additional supports such as adoption assistance and pet-related leave reinforce this emphasis.
  • Leave & Time Off Breadth Paid time off, seasonal compressed schedules, and flexibility options are highlighted across materials. The ability to start with substantial PTO and buy additional time enhances perceived time-off breadth.

The J.M. Smucker Co. Insights

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The Company
HQ: Orrville, OH
5,001 Employees

What We Do

Each generation of consumers leaves their mark on culture by establishing new expectations for food and the companies that make it. At The J.M. Smucker Co., it is our privilege to be at the heart of this dynamic with a portfolio that appeals to each generation of people and pets with products found in 90 percent of U.S. homes and countless restaurants. This includes a mix of iconic brands consumers have always loved such as Folgers®, Jif® and Milk-Bone® and new favorites like Café Bustelo®, Smucker’s® Uncrustables® and Rachael Ray® Nutrish®. By continuing to immerse ourselves in consumer and pet parent preferences for food, how it’s purchased and how the companies that make it should operate, we will maintain the important role we play in their lives. This will allow us to continue growing our business and the positive impact we have on all of those who count on us.

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