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Metadata Jobs in Ohio (NOW HIRING)

Netflix

Watch Netflix (Tagger): $12-$46

Warren, OH

As a Netflix Tagger, you'll watch movies, TV shows, documentaries, and other original content on Netflix and assign relevant metadata and tags that help improve Netflix's recommendation algorithm.

Eaton

Senior Data Architect

Beachwood, OH · On-site

$130K - $190K/yr

Apply expertise in data governance, metadata management, and data integration to support the creation of scalable and reusable data assets. Work with engineers and analysts to implement data quality ...

The Scotts Company LLC

Data Steward

Marysville, OH · On-site

$87.60K - $103.10K/yr

Metadata Management: Manage and enhance metadata repositories, documenting data lineage, definitions, and relationships. Work closely with stakeholders to ensure accurate and comprehensive metadata ...

The Scotts Miracle Gro Company

Data Steward

Marysville, OH · On-site +1

$87.60K - $103.10K/yr

Metadata Management: Manage and enhance metadata repositories, documenting data lineage, definitions, and relationships. Work closely with stakeholders to ensure accurate and comprehensive metadata ...

A-TEK Inc.

Senior Data Engineer

Continental, OH · On-site +1

$160K - $170K/yr

Develop metadata-driven automation, data quality validation, lineage tracking, and governance capabilities * Build and maintain reporting, analytics, and dashboarding solutions supporting operational ...

Huntington

Project Delivery Analyst

Columbus, OH · On-site +1

Support implementation of metadata including capture, storage and management of business, technical and operational metadata. Perform data discovery, profiling, and root cause analysis on high ...

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How much do metadata jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for metadata in Ohio is $14.96, according to ZipRecruiter salary data. Most workers in this role earn between $11.20 and $16.68 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Metadata Specialist, and why are they important?

To thrive as a Metadata Specialist, you need strong organizational skills, attention to detail, and knowledge of metadata standards and cataloging principles, often supported by a degree in library science, information science, or a related field. Familiarity with cataloging tools, metadata management systems, and standards like Dublin Core or MARC is typically required. Excellent communication, problem-solving abilities, and collaboration skills help you work effectively with cross-functional teams and stakeholders. These skills ensure accurate data organization and retrieval, which are critical for maintaining data integrity and supporting information discovery.

What are some typical challenges faced by metadata specialists when managing large datasets, and how can they be addressed?

Metadata specialists often encounter challenges such as inconsistent data standards, incomplete metadata entries, and integrating metadata from multiple sources. These issues can make it difficult to ensure data discoverability and usability. Addressing them typically involves establishing clear metadata standards, using automated tools for validation, and collaborating closely with data owners and IT teams to maintain consistency. Regular training and documentation updates also help in keeping metadata practices aligned across the organization.

What are metadata specialists?

Metadata specialists are professionals responsible for creating, managing, and maintaining metadata, which is data that describes and provides information about other data. They work to ensure that digital assets, documents, or datasets are accurately categorized, searchable, and retrievable by assigning standardized descriptions and tags. Metadata specialists often work in libraries, archives, museums, or organizations with large digital collections, and play a key role in data governance and information management.

What are 5 examples of metadata?

Metadata for a Metadata professional refers to data that describes other data, such as file size, creation date, author, file format, and keywords. These examples help organize, find, and manage digital information efficiently. Understanding and managing metadata is essential in data management, digital archiving, and information retrieval tasks.

What is the difference between Metadata vs Data Analyst?

AspectMetadataData Analyst
Required CredentialsKnowledge of data management, basic understanding of databasesBachelor's degree in statistics, data science, or related field
Work EnvironmentData management teams, IT departmentsBusiness, finance, marketing teams
Employer & Industry UsageUsed across industries for data catalogingUsed in analytics, reporting, decision-making
Common Search & ComparisonUnderstanding data structureAnalyzing data for insights

Metadata involves managing data about data, such as descriptions and structure, while a Data Analyst interprets data to provide insights. Both roles are essential in data management but serve different functions within organizations.

What are the most commonly searched types of Metadata jobs in Ohio? The most popular types of Metadata jobs in Ohio are:
What are popular job titles related to Metadata jobs in Ohio? For Metadata jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Metadata jobs in Ohio look for? The top searched job categories for Metadata jobs in Ohio are:
What cities in Ohio are hiring for Metadata jobs? Cities in Ohio with the most Metadata job openings:
Metadata jobs near you
Director, Data Platforms

Director, Data Platforms

Highlights for Children

Columbus, OH

Other

Posted 11 days ago

Job description

Director of Data Platforms
Highlights for Children is advancing a major digital and data transformation to enhance customer engagement, inspire innovation, and accelerate decision-making across the enterprise removing our dependency on the highly customized current system. The Director of Data Platforms will be the strategic and technical leader responsible for evolving our enterprise data platform into a modern, scalable, AI-ready ecosystem built on Microsoft Fabric and Azure. They will be accountable for delivering platform capabilities on time, on target, and on budget, establishing a culture of execution excellence and measurable outcomes.
Reporting to the SVP of IT, the Director of Data Platforms will guide a multidisciplinary team of engineers and architects, from the internal team and vendor partners. They will operate the data platform as a product, delivering reliable, governed, high-quality data capabilities that empower business teams, enable personalization and analytics, support digital product experiences, and unlock new value for the organization.
This role blends strategic partnership with hands-on expertise. We're looking for a hands-on leader who will work closely with stakeholders driving phased migrations with parallel legacy run, rigorous testing, and zero-disruption standards. They will shape platform direction, drive engineering excellence, steward governance practices, and champion a modern data culture across Highlights.
Key Responsibilities
Data Platform Strategy & Leadership
  • Co-develop and execute the enterprise data platform strategy in partnership with the SVP of IT and cross-functional business leaders.
  • Operate the data platform with a product mindset, owning the platform roadmap, backlog, release plans, and service quality.
  • Align platform capabilities with business priorities, enabling measurable impact tied to customer engagement, revenue opportunities, cost optimization, and innovation.
  • Champion responsible and ethical data use, ensuring the platform supports privacy, compliance, and trustworthy AI outcomes.
  • Ensure platform design supports Highlights' unified customer and household data needs, including cross-product identity resolution, metadata-rich lineage, and trustworthy personalization across channels.
Platform Modernization & Engineering Excellence
  • Lead the modernization and continuous enhancement of Highlights' enterprise data platform using Microsoft Fabric, Azure, and modern engineering patterns.
  • Oversee platform services that support scalable ELT/ETL pipelines, orchestration frameworks, real-time/event-driven data flows, semantic modeling, and reusable data products.
  • Architect and deliver platform features that support AI/ML workloads, including model pipelines, feature stores, vectorized data storage, and AI-ready data access patterns.
  • Drive reliability, observability, data quality, performance, and SLAs through modern DataOps and Site Reliability Engineering practices.
  • Lead risk-assessed, zero-data-loss migrations from legacy systems using automated testing, dual-run validation, and lineage auditability ensuring uninterrupted operations for our subscription, eCommerce, and multi-channel customer experiences.
  • Oversee the integration and unification of multi-source customer/household data (buyer, parent, child, educator) to support cross-channel engagement, subscription optimization, and personalization.
Platform-Enabled Data Governance & Quality
  • Advance enterprise data governance by integrating stewardship, ownership, metadata, and data quality controls directly into platform capabilities.
  • Implement automated governance and quality tooling-metadata services, lineage, cataloging, profiling, quality checks to create trustworthy, certified data products.
  • Ensure metadata, lineage, and household-level identity are embedded into the platform to support trustworthy decision-making and personalized customer experiences across Highlights' brands.
Cross-Functional Partnership & Influence
  • Be a strategic partner with Product, Marketing, Operations, Analytics, Finance, and Enterprise Applications to translate business needs into platform capabilities.
  • Work closely with the Director of Analytics to ensure seamless integration between the data platform and analytics/reporting ecosystems.
  • Communicate platform direction, progress, risks, and value clearly to executive stakeholders-translating complex technical concepts into business outcomes.
  • Build and leverage a strong internal and external professional network-including vendor partners, industry practitioners, and Microsoft ecosystem peers-to accelerate problem-solving and strengthen platform maturity.
Leadership, People, and Team Development
  • Lead, mentor, and develop a multidisciplinary data platform team including data engineers, platform engineers, and data architects.
  • Provide hiring authority and budget ownership to shape a high-performing, scalable team aligned with transformation goals.
  • Serve as a change agent, fostering a data-driven mindset, challenging legacy processes, and driving adoption of modern engineering and governance practices.
  • Maintain a hands-on role when necessary-supporting architecture decisions, troubleshooting complex platform issues, and guiding strategic proofs of concept.
Required Qualifications
Technical Expertise
  • Proven experience modernizing enterprise data platforms using Microsoft Fabric and Azure cloud services.
  • Strong data architecture background with expertise across data modeling, platform patterns, governance tooling, and large-scale data systems.
  • Hands-on experience with ELT/ETL pipelines, orchestration, event-driven architectures, APIs, and real-time data flows.
  • Experience enabling ML engineering and data science teams through platform capabilities such as feature stores, model pipelines, and AI-ready data patterns.
  • Deep understanding of data governance frameworks, metadata management, data quality automation, and responsible data practices.
  • Familiarity with observability, monitoring, and reliability practices for data platforms.
  • Track record of owning platform security posture, including proactive risk identification, mitigation planning, incident response readiness, and security-by-design practices in partnership with Information Security.
  • Demonstrated ability to integrate identity, lineage, and metadata to support unified buyer/user/household data and personalized multi-channel customer experiences.
Leadership & Business Skills
  • Demonstrated success leading data engineering or data platform teams in a modernizing IT environment.
  • Ability to connect technical platform decisions to business outcomes and KPIs.
  • Strong communication, storytelling, and influence skills-comfortable engaging with both executives and technical teams.
  • Experience managing vendors, leveraging your professional network, evaluating emerging technologies, and optimizing platform spend and performance.
  • Ability to activate external networks: industry experts, vendors, peer communities-to accelerate learning curves and enhance platform quality.
Preferred Experience
  • Consumer, subscription-based, publishing, or digital product environments.
  • Background in customer engagement, personalization, or content-driven data use cases.
Expected Outcomes (First 12-18 Months)
  • A modern, scalable enterprise data platform is fully operational on Microsoft Fabric, replacing fragmented legacy components and serving as the foundation for the future.
  • Seamless legacy-to-Fabric migration achieved with zero data loss, no service disruptions, and ≥99.9% data accuracy, supported by automated testing, dual-run validation, and robust observability
  • Platform reliability, performance, and cost transparency materially improved, with clearly defined SLAs/SLOs, proactive monitoring, and predictable operating costs aligned to business usage.
  • Enterprise data governance embedded directly into the platform, including metadata, lineage, quality controls, and stewardship-resulting in trusted, certified data products used confidently across the organization enabling subscription optimization by turning subscriber data into a trusted, actionable asset-powering pricing, retention, personalization, and growth decisions at scale.
  • Unified, cross-channel customer and household data models established, enabling consistent reporting, trustworthy personalization, and improved subscription and engagement insights.
  • AI- and analytics-ready data capabilities delivered, supporting responsible experimentation, automation, and future ML use cases without compromising security or privacy.
  • Reusable data products and real-time data capabilities adopted by business teams, reducing manual reporting effort and accelerating decision-making across the enterprise.
  • A high-performing data platform team in place, operating with strong engineering discipline, clear ownership, effective vendor partnerships, and a culture of execution delivering outcomes on time, on target, and on budget that has clear impact on the IT team and business performance
  • Strong cross-functional trust and adoption achieved, with business partners viewing the data platform as a reliable, strategic asset rather than a bottleneck.
  • Operational customer 360 and unified household identity models enabling cross-channel personalization and subscription optimization.
  • You've built strong relationships with peers and stakeholders, resulting in strong adoption of modern data platform practices across IT and business teams.

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