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Data Operations Jobs in Ohio (NOW HIRING)

EASE Logistics

Data Engineer

Dublin, OH · On-site

$108K - $129K/yr

... data operations and deployment processes using CI/CD pipelines and infrastructure-as-code (e.g., ARM, Bicep, or Terraform). · Stay current with emerging Azure technologies and recommend improvements ...

AVI Foodsystems

Head of Data & Analytics

Warren, OH · On-site

The Mission: Transform the company's data from a "back-office cost center" into a "strategic enterprise asset." This leader will oversee the decommissioning of legacy financial systems, the ...

Paychex

Data Solutions Engineer

Cincinnati, OH · On-site +1

$91K - $156K/yr

Work with architects, operations teams, and data scientists to define data requirements and translate them into actionable data strategies. Design, build and optimize data systems for performance ...

Paychex

Data Solutions Engineer

Cincinnati, OH · On-site

$91K - $156K/yr

Work with architects, operations teams, and data scientists to define data requirements and translate them into actionable data strategies. Design, build and optimize data systems for performance ...

Concora Credit Inc.

Operations Data Analyst

Akron, OH · On-site

Overview As our Operations Data Analyst, you'll help drive Concora Credit's Mission to enable customers to Do More with Credit - every single day. The impact you'll have at Concora Credit: The ...

Concora Credit Inc.

Operations Data Analyst

Akron, OH · On-site

Overview As our Operations Data Analyst, you'll help drive Concora Credit's Mission to enable customers to Do More with Credit - every single day. The impact you'll have at Concora Credit: The ...

Huntington

Data Lake Administrator (AWS)

Columbus, OH · Hybrid

The Data Lake Administrator is responsible for the administration, security, availability, and operational health of the enterprise AWS-based data lake platform. This role focuses on day-to-day ...

Huntington

Data Lake Administrator (AWS)

Columbus, OH · Hybrid

The Data Lake Administrator is responsible for the administration, security, availability, and operational health of the enterprise AWS-based data lake platform. This role focuses on day-to-day ...

Woodward

$136K - $168K/yr

Salary will be determined by the applicant's education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data. Operations Manager SERVO ...

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All JobsData Operations JobsData Operations Jobs in Ohio

Data Operations information

See Ohio salary details

$49.4K

$122.2K

$190.1K

How much do data operations jobs pay per year?

As of Jun 16, 2026, the average yearly pay for data operations in Ohio is $122,189.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,400.00 and $155,400.00 per year, depending on experience, location, and employer.

What is a Data Operations job?

A Data Operations job involves managing and optimizing the processes, tools, and workflows that ensure the efficient movement, storage, and accessibility of data. This includes data ingestion, transformation, quality assurance, and pipeline monitoring to support analytics and business intelligence. Data Operations professionals collaborate with engineers, analysts, and business teams to improve data reliability, scalability, and performance. Their role is critical in maintaining clean, accessible, and well-governed data for decision-making.

What jobs pay 500,000 a year in the US?

In the US, high-paying roles such as senior executives, investment bankers, specialized surgeons, and successful entrepreneurs can earn $500,000 or more annually. These positions often require advanced skills, extensive experience, and sometimes significant risk or ownership stakes.

What is the role of data operations?

Data operations involve managing, processing, and maintaining data to ensure its accuracy, availability, and security for organizational use. Professionals in this field often work with data management tools, databases, and data quality standards to support analytics and decision-making processes.

Is 30 too late for data science?

Data operations roles often value relevant skills and experience over age, and many professionals transition into data science at various stages of their careers. While some roles may prefer candidates with recent technical training or certifications, age is generally not a barrier if you develop strong analytical, programming, and data management skills. Continuous learning and practical experience can help you succeed regardless of age.

What types of teams and departments does Data Operations typically collaborate with?

Data Operations professionals often work closely with data engineering, business intelligence, IT, and analytics teams, as well as stakeholders from various business units such as marketing, finance, and operations. Their role frequently involves coordinating data pipelines, troubleshooting data quality issues, and ensuring smooth integration across systems. This cross-functional collaboration helps align data efforts with organizational goals and supports informed decision-making throughout the company. Being adaptable and communicative is key, as you'll regularly facilitate the flow of data and insights between technical teams and business users.

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

To thrive in Data Operations, you need strong analytical skills, data management experience, and a background in fields like information systems, computer science, or statistics. Familiarity with data visualization tools (e.g., Tableau), database management systems (e.g., SQL), and data integration platforms, along with relevant certifications such as AWS or Microsoft Azure Data Engineer, are highly valuable. Exceptional attention to detail, problem-solving ability, and effective collaboration skills differentiate top performers in this role. These competencies ensure accurate data flow, system integrity, and seamless cross-team cooperation, all of which are critical for maintaining reliable business operations.

What jobs pay 200,000 a year in the USA?

In data operations, senior roles such as Data Operations Managers, Data Architects, and Data Engineering Directors can earn $200,000 or more annually, especially with extensive experience, advanced skills in SQL, Python, or cloud platforms, and leadership responsibilities. These positions often require a strong understanding of data management, analytics, and sometimes certifications like CDMP or AWS certifications.
What are the most commonly searched types of Data Operations jobs in Ohio? The most popular types of Data Operations jobs in Ohio are:
What are popular job titles related to Data Operations jobs in Ohio? For Data Operations jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Data Operations jobs in Ohio look for? The top searched job categories for Data Operations jobs in Ohio are:
Data Operations jobs near you
Infographic showing various Data Operations job openings in Ohio as of June 2026, with employment types broken down into 90% Full Time, 5% Contract, and 5% Nights. Highlights an 84% In-person, and 16% Hybrid job distribution, with an average salary of $122,189 per year, or $58.7 per hour.
Data Engineer

Data Engineer

EASE Logistics

Dublin, OH • On-site

$108K - $129K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

JOB SUMMARY: We are seeking a skilled Data Engineer to join our Analytics & Automation team and serve as the primary architect and builder of our data pipelines. This role will be responsible for designing, implementing, and maintaining scalable, cost-effective data solutions that power enterprise analytics and reporting. The ideal candidate will work closely with business stakeholders to identify data needs, ensure high data quality, and optimize our use of Azure-based technologies for ongoing innovation and performance.

ESSENTIAL DUTIES

· Design, build, and maintain robust, scalable data pipelines in Azure using services such as Azure Data Factory, Azure Synapse, and Azure Data Lake.

· Ingest and integrate data from diverse sources (APIs, databases, files, etc.) into centralized repositories for analytics use.

· Develop and manage ETL/ELT workflows that transform raw data into clean, analytics-ready models aligned with business requirements.

· Create microservices architecture that rapidly scales with business growth and AI capabilities.

· Build data pipelines that feed AI models with clean, structured logistics data.

· Implement real-time analytics engines powering predictive logistics capabilities.

· Ensure data quality, integrity, and governance through validation, monitoring, and alerting systems.

· Collaborate with business and technical teams to gather data requirements and ensure alignment between data assets and business needs.

· Implement cost-conscious data engineering strategies, optimizing performance while managing cloud consumption and storage expenses.

· Maintain and enhance a semantic data layer or curated datasets to support self-service BI (Power BI) and advanced analytics.

· Contribute to the architecture of our data platform, including security, scalability, and performance best practices.

· Automate data operations and deployment processes using CI/CD pipelines and infrastructure-as-code (e.g., ARM, Bicep, or Terraform).

· Stay current with emerging Azure technologies and recommend improvements to existing data workflows

· Other duties as assigned.

QUALIFICIATIONS

Education

· Bachelor’s Degree in an IT-related program OR equivalent with 7+ years of technology experience required.

· Additional related training and certifications will be weighted on a case-by-case basis.

Experience

· 5+ years of hands-on experience in a data engineering or similar role, with a proven track record of building end-to-end data solutions in a cloud-native Microsoft Azure environment, including data ingestion, transformation, and modeling for analytics use cases

· Work experience in the transportation industry is a plus.

Knowledge, Skills, and Abilities

· Proven experience building and managing data pipelines in Microsoft Azure environments.

· Proficiency with tools like Azure Data Factory, Synapse Analytics, Data Lake, and Power BI integration.

· Strong knowledge of SQL, data modeling, and ELT/ETL patterns.

· Experience working with APIs, JSON, and structured/unstructured data sources.

· Demonstrated ability to work cross-functionally to define and deliver high-quality data solutions.

· Strong organizational skills and ability to perform multiple tasks simultaneously, set priorities, work in teams with diverse cultural backgrounds, work independently, and handle conflicting priorities while maintaining consistent, quality work with attention to detail and meet tight deadlines.

· Availability to work a flexible schedule as needed.

· Proficient in Microsoft Office Suite.

· Demonstrated leadership skills, with the ability to effectively communicate and collaborate with cross-functional teams.

· Attention to detail, with a focus on accuracy and compliance in a fast-paced, dynamic environment.

· Logistics / Supply Chain experience preferred.

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