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.
Orrville, OH
Live, first seen by us 50 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s 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
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.
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
- 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
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$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.
Day 50
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- 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
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New Data Leadership postings at the employers we follow are up 7% over the last 5 weeks compared with the 5 before.
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.
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.
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.
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.
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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:
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