Data Architect, Enterprise Data Platform

smucker; Orrville (OH); Hybrid; USD 140,000 - 180,000; Full time

Job summary

Smucker is seeking a Data Architect to design and maintain enterprise data models that enable analytics, reporting, and data-driven decisions. You will define dimensional models, standards, and a unified semantic layer across data domains to support trusted analytics across tools like Tableau.

Responsibilities include modeling, governance, and collaboration with data engineers and business stakeholders to ensure alignment with enterprise standards and performance requirements.

Qualifications

• Bachelor's degree or equivalent in information technology or related field.
• 8+ years in data modeling, data architecture, analytics, or senior data engineering.
• Advanced SQL and experience with large datasets.
• Experience with Databricks, lakehouse architectures, or similar cloud platforms.

Responsibilities

• Design, develop, and maintain dimensional data models using star schema, defining fact and dimension tables.
• Ensure models are optimized for performance, scalability, and usability.
• Create conceptual, logical, and physical data models; profile new data sources.
• Apply enterprise data modeling standards and validate consistency and quality.
• Collaborate with data owners, engineers, and analytics teams to align models with business needs.

Skills

Data Modeling

Star Schema

SQL

Databricks

Lakehouse

Cloud Platforms

Education

Bachelor's degree in IT

Tools

Databricks

Lakehouse

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 th