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Data Automation Engineer Jobs (NOW HIRING)

Senior Automation Engineer

Huntsville, AL · Remote

$106K - $139K/yr

Working as a member of the Synthetic Data & Automation Engineering Team, the Senior Automation Engineer builds scalable automation frameworks, API validation services, continuous integration ...

GenAI Data Automation Engineer Location: Washington, DC (Remote) Type: Contract To Hire Compensation: $48.95 /hr Security Clearance: Public Trust Responsibilities * Design and maintain data pipelines ...

GenAI Data Automation Engineer Location: Washington, DC (Remote) Type: Contract To Hire Compensation: $48.95 /hr Security Clearance: Public Trust Responsibilities * Design and maintain data pipelines ...

GenAI Data Automation Engineer Location: Washington, DC (Remote) Type: Contract To Hire Compensation: $48.95 /hr Security Clearance: Public Trust Responsibilities * Design and maintain data pipelines ...

GenAI Data Automation Engineer Location: Washington, DC (Remote) Type: Contract To Hire Compensation: $48.95 /hr Security Clearance: Public Trust Responsibilities * Design and maintain data pipelines ...

GenAI Data Automation Engineer Location: Washington, DC (Remote) Type: Contract To Hire Compensation: $48.95 /hr Security Clearance: Public Trust Responsibilities * Design and maintain data pipelines ...

Support continuous improvement initiatives and explore opportunities for data automation and ... Strong PLC programming experience, including ladder logic and structured text, with the ability to ...

Support continuous improvement initiatives and explore opportunities for data automation and ... Strong PLC programming experience, including ladder logic and structured text, with the ability to ...

$150 - $200/hr

... automation workflows, you'll scale data analytics to generate actionable, informative conclusions at mission speed. If you are passionate about continuous learning, rapid impact, and engineering ...

Expand What Data & Analytics Can Deliver. Remote | Full-Time | $90,000-$100,000 | High-Impact ... As an Automation Engineer, you'll turn repetitive, manual processes into reliable, scalable ...

Data Automation Manager

Milwaukee, WI · On-site

$125 - $150/hr

Collaborate with Data Engineering, Database, and Architecture teams to architect, develop, and deploy scalable automation, AI, and data quality solutions that support current business needs and ...

$125 - $150/hr

Collaborate with Data Engineering, Database, and Architecture teams to architect, develop, and deploy scalable automation, AI, and data quality solutions that support current business needs and ...

Expand What Data & Analytics Can Deliver. Remote | Full-Time | $90,000-$100,000 | High-Impact ... As an Automation Engineer, you'll turn repetitive, manual processes into reliable, scalable ...

Showing results 21-40

Data Automation Engineer information

See salary details

$37K

$107.1K

$163K

How much do data automation engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for data automation engineer in the United States is $107,126.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,500.00 and $123,500.00 per year, depending on experience, location, and employer.

What is a data automation engineer?

Data Automation Engineers are professionals who design, develop, and maintain automated systems to collect, process, and analyze data. They use programming, scripting, and various data tools to streamline data workflows, reduce manual intervention, and improve efficiency. Their work often involves building data pipelines, integrating data from multiple sources, and ensuring data quality and reliability. By automating repetitive data tasks, they help organizations make faster, data-driven decisions. Data Automation Engineers typically collaborate with data analysts, data scientists, and IT teams to support business objectives.

What are some typical challenges a data automation engineer faces when integrating new automation tools into existing data pipelines?

Data Automation Engineers often encounter challenges related to compatibility and scalability when introducing new automation tools to established data pipelines. Legacy systems may have limitations that require creative solutions to ensure seamless integration without disrupting ongoing processes. Additionally, maintaining data quality and consistency during transitions is critical, as is collaborating with cross-functional teams—such as data analysts, IT, and software developers—to align on requirements and troubleshoot issues. Proactive communication and thorough documentation can help overcome these challenges and ensure successful automation implementation.

What are the key skills and qualifications needed to thrive as a data automation engineer, and why are they important?

To thrive as a Data Automation Engineer, you need strong skills in programming (such as Python or Java), data integration, and database management, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, automation frameworks (like Apache Airflow), and cloud platforms (such as AWS or Azure) is also essential, along with relevant certifications. Attention to detail, problem-solving abilities, and effective communication are key soft skills for identifying automation opportunities and collaborating across teams. These skills are crucial for designing efficient, scalable solutions that streamline data workflows and support business intelligence needs.

What is the difference between Data Automation Engineer vs Data Analyst?

AspectData Automation EngineerData Analyst
Required CredentialsBachelor's in CS, Data Science, or related; knowledge of scripting and automation toolsBachelor's in Statistics, Math, or related; proficiency in data visualization and analysis tools
Work EnvironmentFocus on developing automation pipelines, scripting, and optimizing data workflowsFocus on interpreting data, creating reports, and providing insights
Employer & Industry UsageTech companies, data-driven organizations, IT departmentsMarketing firms, finance, healthcare, research institutions

The main difference is that Data Automation Engineers focus on building and maintaining automated data processes, while Data Analysts interpret data to generate insights. Both roles require strong technical skills, but their core responsibilities differ significantly.

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What cities are hiring for Data Automation Engineer jobs?

Cities with the most Data Automation Engineer job openings:

What states have the most Data Automation Engineer jobs?

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What are popular job titles related to Data Automation Engineer jobs?

For Data Automation Engineer jobs, the most frequently searched job titles are:

Infographic showing various Data Automation Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $107,126 per year, or $51.5 per hour.

Senior Automation Engineer

Huntsville, AL • Remote

$106K - $139K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago


Job description

Benefits:
  • 401(k)
  • 401(k) matching
  • Dental insurance
  • Health insurance
  • Paid time off
  • Vision insurance

Role: Senior Automation Engineer.
Location: 100% Remote.
 
 Job Description:
The Senior Automation Engineer is responsible for designing, developing, and maintaining the automation framework that powers the Synthetic Data & Automation Platform supporting the Community Care Network Next Generation (CCN NG) program. This role develops the automated integration validation capabilities that enable continuous testing, rapid regression analysis, and reliable verification of healthcare transaction processing across the CCN NG product portfolio.
 
Working as a member of the Synthetic Data & Automation Engineering Team, the Senior Automation Engineer builds scalable automation frameworks, API validation services, continuous integration pipelines, and reusable execution components that transform synthetic healthcare transaction data into repeatable integration validation. The role emphasizes engineering automation, platform reliability, and continuous delivery over traditional test script development.
 
Reporting to the Automation & Synthetic Data Architect, the Senior Automation Engineer collaborates closely with the Healthcare Interoperability Engineer, Senior Synthetic Data Engineer, Automation Intelligence Engineer, and Integration Validation Engineer to establish a robust automation platform supporting engineering, integration, and release readiness activities.
 
Description Mission:
Design, develop, and continuously evolve the automation capabilities of the CCN NG Synthetic Data & Automation Platform by delivering scalable frameworks, automated integration validation, and continuous engineering pipelines that improve software quality, accelerate delivery, and reduce operational risk.
EOE
 
Job Responsibilities:
 
Automation Platform Engineering
·    Design, develop, and maintain the automation framework supporting end-to-end integration validation.
·    Build reusable automation components capable of executing healthcare transaction workflows across multiple environments.
·    Develop scalable automation services supporting continuous integration, regression validation, and release readiness.
·    Ensure automation solutions are modular, maintainable, extensible, and reusable across the CCN NG product portfolio.
Integration Validation Automation
 
 
·    Develop automated validation for healthcare transaction lifecycles, including eligibility, claims, payment, and related interoperability workflows.
·    Build API validation services supporting system-to-system integration testing.
·    Automate verification of transaction processing, business rules, and expected outcomes using synthetic healthcare transaction data.
·    Develop automated regression suites that rapidly identify functional or integration defects following system changes.
Engineering Pipeline Integration
 
 
·    Integrate automation capabilities into CI/CD and DevSecOps pipelines.
·    Support continuous validation throughout the software delivery lifecycle.
·    Develop automated reporting, execution metrics, and engineering dashboards.
·    Improve engineering efficiency through automation of repetitive validation activities.
Engineering Collaboration
 
 
·    Partner with the Senior Synthetic Data Engineer to integrate synthetic datasets into automated validation workflows.
·    Collaborate with the Automation Intelligence Engineer to operationalize intelligent engineering workflows within the automation platform.
·    Work closely with the Healthcare Interoperability Engineer to ensure validation logic accurately reflects healthcare business rules and interoperability standards.
·    Support the Integration Validation Engineer by providing reliable automation capabilities that facilitate independent validation and release certification.
Platform Reliability
 
 
·    Monitor, maintain, and continuously improve automation framework performance and reliability.
·    Troubleshoot automation failures and identify opportunities for optimization.
·    Promote engineering best practices supporting maintainability, scalability, and operational excellence.
·    Contribute to architecture discussions regarding automation strategy and platform evolution.
Continuous Improvement
 
 
·    Evaluate emerging automation technologies and engineering tools.
·    Recommend enhancements that improve execution speed, reliability, and maintainability.
·    Develop reusable engineering assets that can be leveraged across multiple development and integration teams.
Required Skills:
 
 
·    Experience designing and developing enterprise automation frameworks.
·    Strong programming experience using Python, Java, C#, or comparable modern programming languages.
·    Experience developing automated API validation and systems integration solutions.
·    Experience implementing CI/CD pipelines and DevSecOps practices.
·    Strong understanding of distributed systems, software architecture, and engineering automation.
·    Excellent analytical, troubleshooting, and collaboration skills.
Desired Qualifications:
 
 
·    Experience supporting healthcare payer, provider, or federal healthcare systems.
·    Familiarity with ANSI X12 healthcare transactions and healthcare interoperability standards.
·    Experience building automated integration validation frameworks.
·    Experience working with containerized applications and cloud-native technologies.
·    Experience using AI-assisted software development tools such as Cursor, GitHub Copilot, or similar engineering platforms.
·    Experience with Infrastructure as Code and automated deployment practices.
·    Experience working within Agile software development environments.
Desired Technical Skills
 
 
·    Python, Java, C#, or comparable programming languages
·    API development and validation
·    RESTful services
·    Integration automation frameworks
·    CI/CD platforms
·    DevSecOps practices
·    Git-based source control
·    Containerization (Docker, Kubernetes)
·    Cloud-native application development
·    Test automation frameworks
·    Agile software engineering
Education and Experience:
 
 
·    Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Data Engineering, Information Systems, or a related technical discipline, or equivalent professional experience.
·    Ten (10) or more years of experience, including seven (7) or more years of experience in software engineering, automation engineering, systems integration, or application development.
Success Measures (First 12-18 Months)
The Senior Automation Engineer will be expected to:
 
 
·    Design and deliver the automation framework supporting the CCN NG Synthetic Data & Automation Platform.
·    Implement automated integration validation covering prioritized healthcare transaction workflows using synthetic healthcare transaction data.
·    Integrate automation capabilities into CI/CD pipelines, enabling continuous validation and rapid regression analysis.
·    Develop reusable automation services and engineering components that improve platform scalability, maintainability, and operational efficiency.
·    Reduce manual engineering effort through reliable automation while improving software quality and release confidence.
·    Collaborate across the Synthetic Data & Automation Engineering Team to ensure automation capabilities seamlessly support synthetic data generation, intelligent engineering workflows, and independent integration validation.
·    Continuously enhance the automation platform through innovation, standardization, and adoption of modern engineering practices.

This is a remote position.