Data Architect, Enterprise Data Platform

The J.M. Smucker Co.; Orrville (OH); Hybrid; USD 130,000 - 180,000; Full time

Job summary

The J.M. Smucker Co. is seeking a Data Architect for the Enterprise Data Platform to design and maintain scalable dimensional data models that power analytics and reporting.

You will enforce semantic consistency and governance while enabling trusted insights across tools like Tableau. In this role you will collaborate with data engineers, analytics teams, and business stakeholders to ensure alignment of source, engineered, and published data layers, supporting enterprise analytics standards.

Qualifications

• Bachelor's degree or equivalent in IT or related field.
• 8+ years in data modeling/architecture or senior data engineering.
• Strong SQL and large dataset experience.
• Ability to translate business needs into data models and governance.
• Experience with modern cloud data platforms and data catalogs.

Responsibilities

• Design, develop, and maintain enterprise dimensional data models.
• Ensure data models align with governance and semantic standards.
• Collaborate with data engineers and analytics teams to implement models and pipelines.
• Assist architecture reviews and provide guidance on analytics architecture.
• Support data governance, metadata, and lineage initiatives.

Skills

Advanced SQL

Cross-functional collaboration

Critical thinking

Communication skills

Data modeling

Semantic design

Education

Bachelor’s degree in Information Technology or related field

Tools

Databricks

ER/Studio

Erwin

Atlan (data catalog)

Git

Azure DevOps

Job description

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.

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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.