Back to jobs

Data Architect, Enterprise Data Platform

Pay
Pay not listedSimilar roles state $154K–$226K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design and maintain star-schema models with fact and dimension tables

  • Validate models for consistency and fix duplication and quality issues

  • Build and maintain a consistent semantic layer with standard metrics

  • Guide pipeline teams so builds match approved data models

  • Document models, definitions, lineage and governance standards

From the employer’s posting
Design, develop, and maintain dimensional data models using star schema methodology
Validate data models for consistency, accuracy, and alignment with business requirements.
Establish and maintain a consistent semantic layer, including standardized metrics, dimensions, and business logic
Collaborate with Data Engineers to ensure data pipeline implementations align with the intent of approved data models
Define and document data models, including structure, definitions, and usage guidance.

What you’ll bring

All qualifications

Core experience

  • Bachelor’s degree, equivalent experience or specialized training in Information Technology
  • Experience designing data models, metadata structures, and semantic foundations that support trusted analytics, reporting, and emerging AI use cases
  • 8+ years of experience in data modeling, data architecture, analytics, or senior data engineering environments
  • Experience with Databricks, lakehouse architectures, or similar modern cloud data platforms
  • Demonstrated ability to collaborate effectively across technical teams, business stakeholders, and data domain partners to drive alignment and adoption
  • Strong understanding of data structures, relationships, and performance optimization
Qualification wording
Bachelor’s degree, equivalent experience or specialized training in Information Technology
Experience designing data models, metadata structures, and semantic foundations that support trusted analytics, reporting, and emerging AI use cases
8+ years of experience in data modeling, data architecture, analytics, or senior data engineering environments
Experience with Databricks, lakehouse architectures, or similar modern cloud data platforms
Demonstrated ability to collaborate effectively across technical teams, business stakeholders, and data domain partners to drive alignment and adoption
Strong understanding of data structures, relationships, and performance optimization
Education & alternatives
- 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
Apply at Smucker

Posting record

Report an error
Status in our records
Live
First seen by us
Sep 18, 202650 days ago
Recorded sightings
107
Last seen by us
Nov 7, 2026
Employer says posted
Sep 16, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$154K–$226K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,013 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 50

Similar jobs usually come down between day 7 and day 55.

From 8,348 similar postings that came down. Coming down is not always a hire.

Smucker is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Azure
  • Databricks
  • Tableau
Where the posting names them
- 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)
- 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
- 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
- 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
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

Your next step

Complete your application on smucker.wd5.myworkdayjobs.com. The employer’s form will show what is required.

Applying through Workday

  • You create an account with each employer before you can upload anything. Every Workday employer has its own account, so one sign-up doesn’t carry over.
  • “Autofill with Resume” comes right after sign-in, before the My Information and My Experience steps. Check every field it fills in those steps, since that’s what recruiters see.
  • Your application status lives in that employer’s Candidate Home, under the same sign-in.

Already applied? Track this application

About Smucker

People
About 400 in 2026.Annual report (SEC Form 10-K)
Company
Listed as SJM.

Demand for Data Leadership roles

New Data Leadership postings at the employers we follow are up 7% over the last 5 weeks compared with the 5 before.

Weekly new Data Leadership postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 789, the most 1,205, and the latest week had 836.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

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. 

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Orrville, OH

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:
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.