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Data Modeling Jobs in Ohio (NOW HIRING)

... models, and supporting infrastructure Define CI/CD patterns for promoting data and analytics assets Data Engineering Design and implement metadata-driven batch ingestion frameworks Develop up to 10 ...

... models, and supporting infrastructure Define CI/CD patterns for promoting data and analytics assets Data Engineering Design and implement metadata-driven batch ingestion frameworks Develop up to 10 ...

Senior Data Engineer

Cleveland, OH · On-site +1

$102K - $139K/yr

Database & Modeling: Strong understanding of database concepts, data design, data modeling, and ETL workflows. * ETL Lifecycle: Experience in analyzing, designing, and coding ETL programs including ...

OH

$102K - $139K/yr

Database & Modeling: Strong understanding of database concepts, data design, data modeling, and ETL workflows. * ETL Lifecycle: Experience in analyzing, designing, and coding ETL programs including ...

Strong knowledge of data warehousing concepts and dimensional modeling. * Experience with big data technologies (Spark, Hadoop, Databricks - optional but preferred). * Familiarity with CI/CD, DevOps ...

Develop advanced analytics models, dashboards, and reporting frameworks that provide actionable ... Ensure high data quality, governance, security, and performance optimization across all client ...

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Data Modeling information

See Ohio salary details

$9

$55

$79

How much do data modeling jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for data modeling in Ohio is $55.82, according to ZipRecruiter salary data. Most workers in this role earn between $50.05 and $64.90 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Modeling position, and why are they important?

To thrive in Data Modeling, you need strong analytical skills, proficiency in database design, and a solid understanding of data structures, usually supported by a degree in computer science, information systems, or a related field. Expertise with tools such as ERwin, SQL, PowerDesigner, or similar data modeling software, as well as knowledge of normalization techniques and experience with data warehousing concepts, are highly valued. Effective communication, attention to detail, and problem-solving abilities set outstanding data modelers apart, allowing them to convey complex concepts to both technical and non-technical stakeholders. These skills are vital for building accurate, scalable data models that serve as the foundation for reliable data-driven decision-making within organizations.

What are the four types of data modeling?

Data modeling in data analysis and database design typically includes four main types: conceptual, logical, physical, and dimensional modeling. Conceptual models define high-level data structures, logical models specify detailed structures without physical considerations, physical models translate logical models into actual database schemas, and dimensional models are used in data warehousing for analytical purposes. Data modelers often use tools like ER diagrams and require understanding of database systems and business requirements.

What is a Data Modeling job?

A Data Modeling job involves designing and structuring data to ensure it is organized, efficient, and scalable for business needs. Data modelers create conceptual, logical, and physical data models that define relationships between data elements. They work closely with database administrators, data engineers, and analysts to optimize data storage and retrieval. Their role is crucial for maintaining data integrity and supporting business intelligence and analytics initiatives. Skills in SQL, database design, and data normalization are essential for success in this role.

What does a typical day look like for someone working in Data Modeling?

A typical day in Data Modeling often involves collaborating with business analysts, database administrators, and software developers to understand data requirements and translate them into logical and physical data structures. Data modelers spend time designing, reviewing, and optimizing data models, ensuring accuracy and consistency across systems and projects. They also review data flows, document data dictionaries, and participate in meetings to align data architecture with overall business needs. The role frequently requires balancing independent technical work with teamwork, as well as responding to feedback and evolving project requirements to support organizational goals.

Information Architect - Data Governance COE

Huntington

Columbus, OH • On-site, Remote

$60 - $77/hr

Full-time

Posted 14 hours ago


Job description

Description

Summary:

The Information Architect, Data Governance COE plays a critical role in designing and maintaining the enterprise information architecture essential for cataloging Huntington’s data for self-service understanding. This role defines and enforces standards for data modeling, taxonomy, and semantic structures to ensure consistency, interoperability, and clarity across the organization. The Information Architect partners closely with business and technology teams to develop and maintain the enterprise data domain model and ontologies that support governance frameworks to enable trusted data usage. Success in this role requires the ability to translate complex theoretical concepts into scalable, governed information structures that drive adoption of the data catalog and deliver measurable value to colleagues.

Duties and Responsibilities:

  • Lead the development and maintenance of the data domain model, taxonomy, and ontologies to ensure shared understanding, semantic consistency, and discoverability of data assets.
  • Operationalize data model and taxonomy through the Enterprise Data Catalog (Alation).
  • Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures to ensure consistency and interoperability across business domains.
  • Provide authoritative guidance on semantic conflicts—resolve definition discrepancies, harmonize terms, and mediate cross-domain dependencies.
  • Contribute to the enterprise data product framework by defining domain boundaries and shared dimensions for cross-domain interoperability.
  • Confirm and document prioritized metadata elements for key business processes and ensure alignment with governance standards.
  • Identify simplification opportunities—reduce redundancy, converge overlapping datasets, and promote canonical sources to improve trust and efficiency.
  • Serve as a thought partner to the Data Governance Community of Excellence—provide insights from modeling and catalog adoption to shape governance strategy and roadmaps.

Basic Qualifications:     

  • Bachelor’s degree in business Intelligence, Data Science, Computer Science, Engineering, or equivalent experience 
  • 10+ years of experience working with data, metadata and reference data frameworks, and experience in metadata and/or data quality monitoring 
  • 7+ years of experience leading work efforts and managing toward deadlines, and developing high-performing teams
  • 5+ years of related experience in strategy, management consulting, or similar skillset

Preferred Qualifications:

  • Experience leading the development of enterprise business glossaries, domain models, and ontologies to enable semantic consistency and shared understanding.
  • Demonstrated experience with data management concepts including data governance, data quality, master data management, data lineage, and metadata management.
  • Proven ability to establish and operationalize metadata governance functions, including policy, standards, roles, and controls.
  • Demonstrated verbal and written communication skills, with strong data and governance storytelling that influences adoption.
  • Hands-on experience implementing and scaling an Enterprise Data Catalog or metadata repository (Alation or equivalent), including curation workflows, stewardship assignments, and adoption strategies.
  • Strong business acumen in relating data to business process drivers and performance management, with a value delivery mindset.
  • Collaborative, team-focused delivery experience that drives outcomes across enterprise and data organizations.
  • Strategic thinker with the ability to translate enterprise objectives into actionable plans and measurable outcomes.
  • Excellent knowledge of data and metadata management principles, business analysis, and process engineering.
  • Crisp business execution and project management rigor, with a strong customer service philosophy.


Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay)

Yes

Workplace Type:

Office

Our Approach to Office Workplace Type

Certain positions outside our branch network may be eligible for a flexible work arrangement. We’re combining the best of both worlds:  in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.

Huntington is an Equal Opportunity Employer.

Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.

Note to Agency Recruiters:  Huntington Bank will not pay a fee for any placement resulting from the receipt of an unsolicited resume.  All unsolicited resumes sent to any Huntington Bank colleagues, directly or indirectly, will be considered Huntington Bank property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.