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Dataops Jobs (NOW HIRING)

Senior DataOps Engineer

Charlotte, NC · On-site

$119.60K - $157.70K/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 ...

Senior DataOps Engineer

Charlotte, NC · On-site

$102.10K - $140.20K/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 ...

Data Engineer with DevOps Skill

Dearborn, MI · On-site

$105.20K - $126.30K/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 ...

Director, Data Operations

Tempe, AZ · On-site

$157K - $197K/yr

Own all DataOps functions directly supporting the claims platform, including eligibility, claims, accumulators, and downstream operational data files. * Serve as the executive owner for how ...

Director, Data Operations

Tempe, AZ · On-site

$157K - $197K/yr

Own all DataOps functions directly supporting the claims platform, including eligibility, claims, accumulators, and downstream operational data files. * Serve as the executive owner for how ...

Director, Data Operations

Tempe, AZ · On-site

$157K - $197K/yr

Own all DataOps functions directly supporting the claims platform, including eligibility, claims, accumulators, and downstream operational data files. * Serve as the executive owner for how ...

We are seeking a DataOps Lead to own and advance the operational reliability, quality, and scalability of our cloud-based data platforms . This role sits at the intersection of data engineering ...

Leverage tools for DataOps (CI/CD) Requirements * Bachelor's degree in Computer Science, Data Science, or related field * 8+ years of work experience; 10+ years of experience in related work if no ...

We are seeking a DataOps Lead to own and advance the operational reliability, quality, and scalability of our cloud-based data platforms . This role sits at the intersection of data engineering ...

We are seeking a DataOps Lead to own and advance the operational reliability, quality, and scalability of our cloud-based data platforms . This role sits at the intersection of data engineering ...

Leverage tools for DataOps (CI/CD) Requirements * Bachelor's degree in Computer Science, Data Science, or related field * 8+ years of work experience; 10+ years of experience in related work if no ...

This role sits within a DataOps team responsible for ensuring data pipelines are accurate, reliable, and delivered on time. You'll work closely with teammates, engineering partners, and operational ...

Sales Engineer

Dallas, TX · On-site

$200K - $250K/yr

Astronomer is on a mission to make DataOps a first-class discipline in every modern data organization. As the driving force behind Apache Airflow, we're powering mission-critical pipelines at scale ...

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Dataops information

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How much do dataops jobs pay per hour?

As of Jun 4, 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 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.

What are 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.

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:
Infographic showing various Dataops job openings in the United States as of May 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 62% In-person, and 38% Remote job distribution, with an average salary of $48,110 per year, or $23.1 per hour.

Senior DataOps Engineer

Scout Motors

Charlotte, NC • On-site

$119.60K - $157.70K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 21 days ago


Job description

About the Team

The Data Platform Team at Scout is dedicated to unlocking the full potential of data by building a secure, scalable, and distributed platform that enables real-time insights, drives informed decision-making, and fosters innovation across the organization.

Our mission is to empower teams with actionable intelligence by streamlining data sharing, ensuring regulatory compliance, maintaining data integrity, and optimizing costs at every level.

This role is focused on building foundation for deploying AI-enabled use cases across company operations.

What you'll do

Become part of an iconic brand that is set to revolutionize the electric pick-up truck & rugged SUV marketplace by achieving the following:

  • 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.

Location & Travel Expectations:

  • This role is based out of the Scout Motors corporate headquarters in Charlotte, NC.
  • The responsibilities of this role require 4-5 days attendance in office with in-person meetings and events regularly. 
  • Applicants should expect that the role will require the ability to convene with Scout colleagues in person and travel to participate in events on behalf of the company from time to time.
What you'll bring 

We expect all Scout employees to have integrity, curiosity, resourcefulness, and strive to exhibit a positive attitude, as well as a growth mindset. You'll be comfortable with change and flexible in a fast-paced, high-growth environment. You'll take a collaborative approach to achieve ambitious goals. Here's what else you'll bring: 

  • 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.
What you'll gain

The benefits of joining Scout include the chance to build products and a company from the ground up.  This is a chance to create something new and lasting - with an iconic brand at its foundation.  In addition, Scout provides competitive compensation and benefits to support your physical, mental, and financial wellbeing. Program specifics are detailed in company policies and employee benefit guides, select highlights:

  • Competitive insurance including:
    • Medical, dental, vision and income protection plans
  • 401(k) program with:
    • An employer match and immediate vesting
  • Generous Paid Time Off including:
    • 20 days planned PTO, as accrued
    • 40 hours of unplanned PTO and 14 company or floating holidays, annually
    • Up to 16 weeks of paid parental leave for biological and adoptive parents of all genders
    • Paid leave for circumstances related to bereavement, jury duty, voting time, or military leave
Pay Transparency

This is a full-time, exempt position eligible to receive a base salary and to participate in an annual performance bonus program. Final salary offered will be determined based on factors including but not limited to the candidate's skills and experience. The annual performance bonus program is preset and not candidate dependent.

Initial base salary range = $140,000.00 - $170,000.00

Initial California base salary range = $154,000.00 - $187,000

Internal leveling code: IC8