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Manager Data Engineering Jobs in Ohio (NOW HIRING)

The Data Engineering Lead plays a critical and strategic role in advancing FMHC's enterprise data ... Oversee table structures, role and permission management, performance tuning, cost optimization ...

The Data Engineering Lead plays a critical and strategic role in advancing FMHC's enterprise data ... Oversee table structures, role and permission management, performance tuning, cost optimization ...

Quanex is looking for a Manager, Data Governance to join our team located in Akron, OH, Owatonna ... This role partners closely with Engineering, IT, Manufacturing, Finance, and Operations ...

Data Engineer

Cincinnati, OH

$109K - $132K/yr

... for data engineering. The ideal candidate will have extensive experience in designing and ... Implement data integration solutions using Azure Data Factory and manage data storage in Azure ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... In data engineering at PwC, you will focus on designing and building data infrastructure and ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... In data engineering at PwC, you will focus on designing and building data infrastructure and ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... In data engineering at PwC, you will focus on designing and building data infrastructure and ...

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Showing results 1-20

Manager Data Engineering information

See Ohio salary details

$29.5K

$92.4K

$163.5K

How much do manager data engineering jobs pay per year?

As of Jun 19, 2026, the average yearly pay for manager data engineering in Ohio is $92,355.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,700.00 and $119,300.00 per year, depending on experience, location, and employer.

What is the difference between Manager Data Engineering vs Data Engineer?

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the key skills and qualifications needed to thrive as a Manager Data Engineering, and why are they important?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

What are Manager Data Engineering roles and responsibilities?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

How does a Manager of Data Engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.
What are the most commonly searched types of Data Engineering jobs in Ohio? The most popular types of Data Engineering jobs in Ohio are:
What job categories do people searching Manager Data Engineering jobs in Ohio look for? The top searched job categories for Manager Data Engineering jobs in Ohio are:
What cities in Ohio are hiring for Manager Data Engineering jobs? Cities in Ohio with the most Manager Data Engineering job openings:
Infographic showing various Manager Data Engineering job openings in Ohio as of June 2026, with employment types broken down into 95% Full Time, 3% Part Time, and 2% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $92,355 per year, or $44.4 per hour.
Manager, Data Engineering

Manager, Data Engineering

J.M. Smucker Company

Orrville, OH • Hybrid

Full-time

Posted 3 days ago


J.M. Smucker rating

8.2

Company rating: 8.2 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

57th of 385 rated food and drinks producers


Job description

Your Opportunity as the Manager, Data Engineering - Enterprise Data Platform

The Manager, Data Engineering is responsible for leading a team of Data Engineers focused on building and operating high-quality data pipelines within a modern cloud data platform. This role combines people leadership, hands-on technical oversight, and operational excellence to deliver trusted, scalable, and efficient data solutions. As part of the Enterprise Data Platforms & Enablement team, this role partners closely with Cloud Engineering, Governance, Architecture, and business stakeholders to support a large-scale transformation from on-premise systems to cloud-native platforms. The Manager ensures that data engineering practices align with modern best practices, including Databricks-based development, medallion architecture (bronze/silver/gold layers), and automated data ingestion frameworks (e.g., Fivetran).

Location: Orrville, OH (Close proximity to Cleveland/Akron)

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:

  • Team Leadership & Delivery

    • Lead, coach, and develop a team of Data Engineers, fostering strong technical skills and ownership

    • Set clear priorities, manage workload, and ensure timely delivery of data engineering initiatives

    • Establish engineering standards, code quality expectations, and best practices across the team

    • Partner with stakeholders to translate business needs into scalable data solutions

  • Data Pipeline Engineering

    • Oversee the design, development, and operation of data pipelines built in Databricks

    • Ensure pipelines are scalable, reliable, and aligned to medallion architecture standards (bronze, silver, gold)

    • Guide implementation of ingestion frameworks using tools like Fivetran and custom ingestion patterns

    • Drive consistent development patterns for batch and near real-time data pipelines

  • Platform & Architecture

    • Provide technical leadership for the Databricks platform, including workspace, jobs, clusters, and performance optimization

    • Collaborate with Cloud Engineering to ensure seamless integration with AWS services (e.g., S3)

    • Ensure alignment with enterprise architecture, including data modeling, partitioning strategies, and storage optimization

    • Optimize compute usage for performance and cost efficiency

  • Data Quality, Governance & Reliability

    • Establish and enforce data quality standards, including testing, validation, and monitoring frameworks

    • Ensure robust observability across pipelines (monitoring, alerting, lineage visibility)

    • Partner with Governance teams to support metadata management and lineage through tools like Atlan

    • Enforce security, compliance, and data access standards across all data engineering assets

  • Operations & Continuous Improvement

    • Own production support processes, including incident management, root cause analysis, and prevention

    • Establish proactive monitoring and health checks for pipelines and platform performance

    • Drive continuous improvement in automation, CI/CD, and release management practices

    • Support and lead data migration efforts from legacy on-prem systems to cloud platforms

What we are looking for:

Minimum Requirements:

  • Bachelor's Degree or equivalent experience

  • 7+ years of experience in data engineering or data platform roles

  • 3+ years of experience leading and developing technical teams

  • Experience operating in modern cloud data environments (Databricks, data lakes, or lakehouse platforms)

  • Proven experience delivering enterprise-scale data pipelines and platforms

  • Experience supporting cloud migration or modernization initiatives

  • Strong expertise in Databricks (notebooks, jobs, cluster management)

  • Proficiency in Python and PySpark for distributed data processing

  • Advanced SQL skills and experience working with large-scale datasets

  • Experience designing and operating cloud-based data platforms (AWS preferred)

  • Experience with data ingestion tools (e.g., Fivetran or similar)

  • Deep understanding of data modeling and medallion architecture patterns

Additional skills and experience that we think would make someone successful in this role (not required):

  • AWS services such as S3, IAM, and data storage architectures

  • Data governance tools such as Atlan or similar

  • Reporting and visualization tools such as Tableau

  • CI/CD tools and automation frameworks

  • Monitoring and observability tools for data platforms

TheRight Placefor 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 ourBasic Beliefs, and we believe in supporting every employee by meeting their physical, emotional, and financial needs.

Stay connected with usonLinkedIn

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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