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J.M. Smucker

Produces jams, peanut butter, breakfast foods

Data Architect - Enterprise Data Platform

Data ManagementConfirmed live in the last 24 hours
Full-timeNo salary listedHybrid

About the Job

Requirements

  • A bachelor's degree, equivalent experience, or specialized training in Information Technology.
  • At least 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 technical and nontechnical audiences.

Responsibilities

  • 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 modeling and architecture decisions.
  • Apply enterprise data modeling standards and best practices across 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.
  • 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.
  • 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.
  • 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.

Desired Qualifications

  • 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, such as Git, GitHub, or Azure DevOps.
  • Understanding of modern data platform concepts and workflows.
  • Understanding of how data architecture, metadata, and governance enable trusted analytics and AI solutions.

About the Company

J.M. Smucker

Produces jams, peanut butter, breakfast foods

Smucker makes and sells a range of everyday foods, including jams and jellies, peanut butter, shortening, and baking products from brands like Smucker’s, Jif, Crisco, Pillsbury, and Hungry Jack. These products solve common cooking and eating needs: jams for breakfasts, peanut butter for sandwiches, shortening for baking and frying, and baking mixes for home cooking. The company stands out through a long history and a portfolio built largely by acquisitions, giving it broad brand recognition and wide distribution in North American grocery channels. Its goal is to grow by expanding its range of pantry staples, preserving trusted brands, and making products more available and convenient for households.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Orrville, OH
Founded
1897

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