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Dataops Jobs (NOW HIRING)

Scout Motors Inc.

Senior DataOps Engineer

Charlotte, NC · On-site

$102K - $140K/yr

The Senior DataOps Engineer will play a crucial role in building a secure and scalable data platform that enables real-time insights and supports AI-enabled use cases across the organization.

Voyager Technologies, Inc.

Senior DataOps Engineer

$107K - $146K/yr

Job Summary The DataOps Engineer is responsible for designing, building, and operationalizing data infrastructure that powers the organization's analytics and business intelligence capabilities. This ...

Guild

Senior DataOps Engineer

$94K - $136K/yr

Position Summary The Senior DataOps Engineer is responsible for executing the organization's data management and storage system strategy ensuring timely access to secure, resilient, scalable, and ...

BTI Solutions

DataOps Engineer

Englewood Cliffs, NJ · On-site

$116K - $140K/yr

DataOps Engineer We are looking for a midlevel engineer to build and operate a data platform that uses Apache Iceberg as the lakehouse table format and Dockerbased microservices (Spark, Flink, Presto ...

BTI Solutions

DataOps Engineer

Englewood Cliffs, NJ · On-site

$116K - $140K/yr

DataOps Engineer We are looking for a mid-level engineer to build and operate a data platform that uses Apache Iceberg as the lake-house table format and Docker-based micro-services (Spark, Flink ...

Btisolutions

DataOps Engineer

Englewood Cliffs, NJ · On-site

$116K - $140K/yr

DataOps Engineer We are looking for a midlevel engineer to build and operate a data platform that uses Apache Iceberg as the lakehouse table format and Dockerbased microservices (Spark, Flink, Presto ...

Scout Motors

Senior DataOps Engineer

Charlotte, NC · On-site

$119K - $157K/yr

Bachelor's degree in computer science, information technology, or related field or equivalent work experience. * 7+ years of hands-on experience as DataOps Engineer in a manufacturing or automotive ...

Scout Motors

Senior DataOps Engineer

Charlotte, NC · On-site

$102K - $140K/yr

Bachelor's degree in computer science, information technology, or related field or equivalent work experience. * 7+ years of hands-on experience as DataOps Engineer in a manufacturing or automotive ...

MM International

Data Engineer with DevOps Skill

Dearborn, MI · On-site

$105K - $126K/yr

Role: DataOps Engineer Location; Hybrid work Dearborn, MI (starting September 1st, will be moving to 4 days a week onsite). Duration: 12 month contract. Additional Information: Hybrid Position ...

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How much do dataops jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for dataops in the United States is $23.13, according to ZipRecruiter salary data. Most workers in this role earn between $17.55 and $24.04 per hour, depending on experience, location, and employer.

What is a DataOps?

DataOps, short for Data Operations, is a set of practices, processes, and technologies that combine data engineering, data integration, and DevOps methodologies to improve the quality and speed of data analytics. DataOps aims to streamline the flow of data from source to value, enabling organizations to deliver reliable, high-quality data to stakeholders more efficiently. This approach emphasizes collaboration, automation, and monitoring throughout the data lifecycle to reduce errors and shorten development cycles. The ultimate goal of DataOps is to create an agile data pipeline that adapts quickly to changing business needs.

What is the difference between Dataops vs Data Engineer?

AspectDataopsData Engineer
Primary FocusAutomating data workflows, deployment, and operational efficiencyBuilding and maintaining data pipelines, storage, and infrastructure
Skills & CertificationsDevOps tools, scripting, cloud platforms, CI/CD practicesSQL, ETL tools, cloud platforms, programming (Python, Scala)
Work EnvironmentCollaborates with DevOps, data teams, and operationsWorks closely with data scientists, analysts, and infrastructure teams
Industry UsageUsed in organizations focusing on data deployment and automationUsed in data infrastructure development and data pipeline creation

While both Dataops and Data Engineers work with data infrastructure, Dataops emphasizes automation, deployment, and operational efficiency, whereas Data Engineers focus on building and maintaining data pipelines and storage systems. Understanding these differences helps organizations assign the right roles for their data needs.

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

To thrive as a DataOps Engineer, you need expertise in data engineering, automation, cloud platforms, and a solid understanding of CI/CD pipelines, typically backed by a degree in computer science or related fields. Familiarity with tools like Apache Airflow, Kubernetes, Docker, Jenkins, and cloud services such as AWS, GCP, or Azure is commonly required, along with knowledge of scripting languages like Python or Bash. Strong collaboration, problem-solving, and communication skills help DataOps professionals work effectively across data, development, and operations teams. These abilities ensure reliable, scalable, and efficient data infrastructure, enabling organizations to quickly deliver high-quality data solutions.

How does a DataOps professional typically collaborate with data engineers, analysts, and other IT teams?

DataOps professionals play a key role in bridging the gap between data engineering, analytics, and IT by facilitating efficient, automated workflows and ensuring data quality across the pipeline. They often work closely with data engineers to streamline data integration and deployment processes, while collaborating with analysts to support timely access to reliable data. Regular communication and cross-functional teamwork are essential, as DataOps is responsible for implementing best practices that help different teams deliver insights faster and with fewer errors. This collaborative environment also encourages continuous feedback and process improvement.
More about Dataops jobs
What cities are hiring for Dataops jobs? Cities with the most Dataops job openings:
What are the most commonly searched types of Dataops jobs? The most popular types of Dataops jobs are:
What states have the most Dataops jobs? States with the most job openings for Dataops jobs include:
What job categories do people searching Dataops jobs look for? The top searched job categories for Dataops jobs are:
Dataops jobs near you
Infographic showing various Dataops job openings in the United States as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $48,110 per year, or $23.1 per hour.

Senior DataOps Engineer

Scout Motors Inc.

Charlotte, NC • On-site

$102K - $140K/yr

Full-time

Re-posted 25 days ago

Job description

Job Summary:
Scout Motors Inc. is dedicated to carrying forward the heritage of iconic American vehicles while embracing innovation. The Senior DataOps Engineer will play a crucial role in building a secure and scalable data platform that enables real-time insights and supports AI-enabled use cases across the organization.
Responsibilities:
• Contribute to the design, implementation, automation, maintenance, and operational support of enterprise-scale cloud data platforms leveraging Databricks, AWS cloud services, and modern Infrastructure as Code (IaC) practices.
• Lead the design, development, optimization, and operational management of enterprise-scale ETL/ELT pipelines within Databricks.
• Build and maintain scalable batch and streaming data pipelines using PySpark, Spark SQL, Delta Lake, and Databricks Workflows.
• Configure, optimize, and manage Databricks clusters for performance, scalability, reliability, and cost efficiency.
• Work closely with software development and systems teams to build Data Integration solutions.
• Design and build Data models using tools such as Lucid, Talend, Erwin, MySQL workbench.
• Define and enhance enterprise data model to reflect relationships and dependencies.
• Review application data systems to ensure adherence to data governance policies.
• Design and build ETL (Python), ELT(Python) infrastructure, automation, and solutions to transform data as required.
• Design and Implement BI dashboards to visualize Trends and Forecasts.
• Design and implement data infrastructure components, ensuring high availability, reliability, scalability, and performance.
• Design, train and deploy ML models
• Implement monitoring solutions to proactively identify and address potential issues.
• Collaborate with security teams to ensure the data platform meets industry standards and compliance requirements.
• Collaborate with cross-functional teams, including product managers, developers, and business partners to ensure robust and reliable systems.
Qualifications:
Required:
• Bachelor's degree in computer science, information technology, or related field or equivalent work experience.
• 7+ years of hands-on experience as DataOps Engineer in a manufacturing or automotive environment.
• Experience with streaming and event-based architecture.
• Experience implementing data lakehouse solutions using Databricks.
• Experience with infrastructure as code (Terraform).
• Proficient in building data pipelines using languages such as Python and SQL.
• Experience with AWS based data services such as Glue, Kinesis, Firehose or other comparable services.
• Experience with Structured, unstructured and time series databases.
• Solid understanding of cloud data storage solutions such as RDS, DynamoDB, DocumentDB, Mongo, Cassandra, Influx.
• Several years of experience working with cloud platforms such as AWS and Azure.
• Proven ability to develop and deploy scalable ML models.
• Hands-on experience in designing, training, and deploying ML models.
• Strong ability to extract actionable insights using ML techniques.
• Ability to leverage ML algorithms for forecasting trends and decision-making.
• Excellent problem-solving and troubleshooting skills. When a problem occurs, you run towards it not away.
• Effective communication and collaboration skills. You treat colleagues with respect. You have a desire for clean implementations but are also humble in discussing alternative solutions and options.
Company:
Scout is more than just a brand, it’s a legacy steeped in a culture of exploration, caretaking, and hard work. Founded in 2022, the company is headquartered in Washington, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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