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Remote Data Engineering Jobs in Ohio (NOW HIRING)

Sr Data Architect, Databricks

Columbus, OH ยท On-site +1

$65 - $87/hr

You will partner closely with engineering, analytics, governance, and business teams to deliver ... full-remote candidate. * McKesson complies with all applicable U.S. immigration laws and ...

Sr Data Architect, Databricks

Columbus, OH ยท On-site +1

$65 - $87/hr

You will partner closely with engineering, analytics, governance, and business teams to deliver ... full-remote candidate. * McKesson complies with all applicable U.S. immigration laws and ...

Feature engineering and dataset preparation * Data versioning tools (e.g., lakeFS) * Metadata ... Weekly pay with full remote flexibility * Professional growth investment, including paid ...

Feature engineering and dataset preparation * Data versioning tools (e.g., lakeFS) * Metadata ... Weekly pay with full remote flexibility * Professional growth investment, including paid ...

Data Engineer

Cincinnati, OH ยท On-site +1

$75K - $145K/yr

... Architecture, Engineering, Construction) and business operational data (BIM models, CAD files ... project schedules/delivery data, finance/resourcing/reforecasting data, IoT/sensor data). * Build ...

Data Engineer

Cleveland, OH ยท On-site +1

$75K - $145K/yr

... Architecture, Engineering, Construction) and business operational data (BIM models, CAD files ... project schedules/delivery data, finance/resourcing/reforecasting data, IoT/sensor data). * Build ...

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Showing results 1-20

Remote Data Engineering information

See Ohio salary details

$42.3K

$123.3K

$168.7K

How much do remote data engineering jobs pay per year?

As of Jun 28, 2026, the average yearly pay for remote data engineering in Ohio is $123,321.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,900.00 and $130,700.00 per year, depending on experience, location, and employer.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote data engineers often work with distributed teams, which requires strong communication and organization skills. They collaborate using tools like Slack, Zoom, and project management platforms to stay aligned on data pipeline development, troubleshooting, and deployment. Regular stand-ups, asynchronous documentation, and clear communication of progress are essential for ensuring everyone is on the same page, regardless of location. Flexibility in working hours and proactive scheduling of meetings help facilitate effective collaboration and project delivery.

What is remote data engineering?

Remote data engineering involves designing, building, and maintaining data systems and pipelines while working from a location outside of a traditional office. Remote data engineers use tools to collect, process, and store large sets of data, making it accessible for analysis and business decision-making. They collaborate with teams virtually, often using cloud-based technologies, to ensure that data infrastructure is reliable, scalable, and secure. This role requires strong technical skills in programming, databases, and data architecture, as well as the ability to communicate effectively in a distributed work environment.

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

To thrive as a Remote Data Engineer, you need strong programming skills (such as Python, Java, or Scala), experience with data modeling, ETL processes, and a solid understanding of database systems, often supported by a degree in computer science or a related field. Proficiency with big data tools like Apache Spark, Hadoop, cloud platforms (AWS, Azure, GCP), and certifications in these technologies is highly valued. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These competencies ensure effective data pipeline development, reliable data management, and seamless teamwork across distributed environments.

What is the difference between Remote Data Engineering vs Remote Data Analyst?

AspectRemote Data EngineeringRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with SQL, Python, cloud platformsBachelor's in Statistics, Data Science, or related; proficiency in Excel, SQL, visualization tools
Work EnvironmentBuilds data pipelines, manages databases, works with cloud infrastructureAnalyzes data sets, creates reports, visualizes data insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, finance, retail, consulting

Remote Data Engineering focuses on designing and maintaining data infrastructure, while Remote Data Analysts interpret data to provide insights. Both roles require strong analytical skills but differ in technical depth and responsibilities.

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 cities in Ohio are hiring for Remote Data Engineering jobs? Cities in Ohio with the most Remote Data Engineering job openings:

Lead ETL Developer- Enterprise Data Warehouse (EDW)

Huntington

Columbus, OH โ€ข On-site, Remote

Full-time

Medical, Life, Retirement, PTO

Posted 15 days ago


Job description

DescriptionOverview

Huntington Bank is seeking a Lead ETL Developer to join our Enterprise Data Warehouse (EDW) team. This role is responsible for leading the design, development, and optimization of scalable data pipelines and solutions that enable the business to leverage data as a strategic asset.

As a technical leader, you will partner across engineering, architecture, QA, and business teams to deliver high-quality, reliable data solutions. You will drive best practices across the SDLC, mentor team members, and help shape the future-state data ecosystem leveraging modern cloud technologies including AWS, Snowflake, and Python-based frameworks.

Key Responsibilities
  • Technical Leadership & Delivery
    • Lead the design, development, and maintenance of ETL/ELT pipelines in the EDW ecosystem
    • Ensure alignment to enterprise data architecture, standards, and best practices
    • Drive solution design from requirements and data mapping documents to scalable technical implementations
  • Development & Engineering Excellence
    • Build and optimize data pipelines using AWS Glue, Snowflake, Python/PySpark, and IBM DataStage
    • Implement reusable, metadata-driven, and performance-optimized data integration patterns
    • Enforce coding standards, version control, and CI/CD practices
  • Data Quality, Testing & Observability
    • Define and implement unit testing, regression testing, and data validation strategies
    • Partner with QA to support system and integration testing efforts
    • Troubleshoot and resolve data and pipeline issues across development, QA, and production environments
  • Collaboration & Communication
    • Work closely with Product Owners, BSAs, architects, and upstream/downstream teams to deliver end-to-end solutions
    • Communicate progress, risks, and blockers clearly to stakeholders and leadership
    • Support production operations, including incident triage and root cause analysis
  • Continuous Improvement & Innovation
    • Identify opportunities to improve performance, reliability, and scalability of data pipelines
    • Contribute to modernization efforts (cloud migration, Snowflake optimization, automation)
    • Stay current on industry trends and emerging technologies in data engineering
  • People Leadership & Mentorship
    • Mentor and coach junior and mid-level developers on technical skills and best practices
    • Provide technical guidance and code reviews to ensure quality and consistency
    • Lead development efforts on key initiatives and serve as a project-level technical lead

Basic Qualifications:

  • Bachelor's Degree
  • 5+ years of ETL/Data Engineering experience in enterprise data warehouse environments or an additional 4 years of related work experience may be considered in lieu of the Bachelor's Degree
  • 5+ years of experience with SQL and Database development.
  • 5+ years of hands on-experience with Python/PySpark and ETL tools.
  • 3+ Years of experience with cloud-based data platforms
Preferred Qualifications
  • Strong understanding of Data Warehousing Concepts, modeling, and SDLC methodologies.
  • Proven experience leading development teams or acting as a technical lead on large-scale data initiatives
  • Experience with AWS services (Glue, S3, EC2) and Snowflake architecture optimization
  • Knowledge of data pipeline observability, monitoring, and automated testing frameworks
  • Experience defining future-state data architecture or modernization roadmaps
  • Familiarity with CI/CD pipelines, DevOps practices, and version control systems
  • Understanding of data governance, security, and regulatory considerations in financial services
  • AWS Certifications (Solutions Architect, DevOps Engineer) preferred
  • Prior experience in banking or financial services industry
What Success Looks Like in This Role
  • Delivers reliable, scalable, and high-performing data pipelines
  • Drives consistency in development standards and SDLC practices across the team
  • Acts as a trusted technical partner across engineering and business stakeholders
  • Elevates team capability through mentorship and structured guidance
  • Actively contributes to modernization and innovation within the EDW platform


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.

Compensation Range:

The compensation range represents the anticipated low and high end of the base compensation range for this position. Actual compensation will vary based on various factors including but not limited to location, experience, and education. Colleagues in this position are also eligible to participate in an applicable incentive compensation plan. In addition, Huntington provides a variety of benefits to colleagues, including health insurance coverage, wellness program, life and disability insurance, retirement savings plan, paid leave programs, paid holidays and paid time off (PTO).

Huntington is an Equal Opportunity Employer.

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

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