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Data Engineering Jobs in Ohio (NOW HIRING)

The Data Engineering Lead plays a critical and strategic role in advancing FMHC's enterprise data transformation and analytics enablement efforts. This role provides technical leadership, direction ...

The Data Engineering Lead plays a critical and strategic role in advancing FMHC's enterprise data transformation and analytics enablement efforts. This role provides technical leadership, direction ...

Data Engineering Manager

Cleveland, OH · On-site

$111K - $133K/yr

The Data Engineering Manager's role is to provide technical leadership for data engineering services including data modeling, data warehouse/lake architecture and administration, ETL pipelines. This ...

The Data Engineering Lead plays a critical and strategic role in advancing FMHC's enterprise data transformation and analytics enablement efforts. This role provides technical leadership, direction ...

A Brief Overview The Manager of Data Engineering at Safelite is responsible for modernizing key legacy data pipelines, focusing on data ingestion, replication, and continuous integration. This role ...

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Data Engineering information

See Ohio salary details

$43.7K

$156.9K

$231.5K

How much do data engineering jobs pay per year?

As of Jul 26, 2026, the average yearly pay for data engineering in Ohio is $156,882.00, according to ZipRecruiter salary data. Most workers in this role earn between $126,900.00 and $161,600.00 per year, depending on experience, location, and employer.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their expertise in tools like SQL, Spark, and cloud platforms remains critical for managing data workflows and ensuring data quality.

What work does a data engineer do?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and optimized for analysis by data scientists and analysts.

What are the typical daily responsibilities of a Data Engineer?

Data Engineers regularly design, build, and maintain scalable data pipelines to support analytics and business intelligence teams. Their daily tasks often involve working with large datasets, optimizing data storage, ensuring data integrity, and troubleshooting data-related issues. Collaboration with data scientists, analysts, and software engineers is common to align on data requirements and improve workflows. You may also participate in regular code reviews and contribute to the ongoing improvement of data infrastructure. This role is ideal for problem-solvers who enjoy working with both code and complex systems in a collaborative, fast-paced environment.

What engineers make 500,000?

Senior data engineers with extensive experience, specialized skills in cloud platforms, and advanced knowledge of data architecture can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes stock options or bonuses.

What is a Data Engineering job?

A Data Engineering job involves designing, building, and maintaining the infrastructure that enables efficient data collection, storage, and processing. Data Engineers develop pipelines to transform raw data into usable formats for analytics and machine learning. They work with databases, big data technologies, and cloud platforms to ensure data is accessible and reliable. Their role is crucial for organizations to make data-driven decisions and optimize business processes.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. They typically require skills in SQL, cloud platforms, and data pipeline tools like Apache Spark or Kafka, making their expertise valuable across many industries. The role is expected to remain strong as organizations continue to prioritize data infrastructure and analytics capabilities.

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

To thrive in Data Engineering, you need a solid background in programming (such as Python, Java, or Scala), data modeling, and database management, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms like AWS or Azure, big data frameworks (e.g., Hadoop, Spark), and relevant certifications is highly valued. Strong problem-solving abilities, effective communication, and the ability to work collaboratively across teams are key soft skills for this role. These attributes are crucial for designing robust data pipelines, ensuring data quality, and enabling organizations to make data-driven decisions efficiently.

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 Data Engineering jobs in Ohio look for? The top searched job categories for Data Engineering jobs in Ohio are:
What cities in Ohio are hiring for Data Engineering jobs? Cities in Ohio with the most Data Engineering job openings:
Infographic showing various Data Engineering job openings in Ohio as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $156,882 per year, or $75.4 per hour.
Manager, Data Engineering

Manager, Data Engineering

J.M. Smucker Company

Akron, OH • Hybrid

Full-time

Posted 11 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

69th of 432 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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