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Dataops Jobs (NOW HIRING)

Patterson-UTI

Data Ops Lead

Houston, TX · On-site

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 ...

Scalepex

Healthcare Data Analyst

Dallas, TX · On-site +1

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 ...

Scalepex

Healthcare Data Analyst

Dallas, TX · Remote

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 ...

Scalepex

Healthcare Data Analyst

Dallas, TX

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 ...

West Advanced Technologies

Azure Data Engineer

Downey, CA · On-site

$118K - $142K/yr

... DataOps. This classification must have a minimum of seven (7) years of applying Enterprise Architecture principles. At least five (5) years of that experience must be in a lead capacity. Q 5 years of ...

Apple

PART DataOps Engineer

Cupertino, CA · On-site

The people here at Apple don't just create products - they create the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the ...

Tech Tammina

DBT Engineer (GCP)

$117K - $140K/yr

Strong Git workflows, CI/CD, and DataOps practices * Proven experience in optimizing and modeling data pipelines on GCP

Astronomer

Sales Engineer

Astronomer empowers data teams with its unified DataOps platform powered by Apache Airflow. The Sales Engineer will lead technical sales efforts, providing tailored solutions and guidance to ...

Apple

PART DataOps Engineer

Cupertino, CA

$118K - $197K/yr

The people here at Apple don't just create products - they create the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the ...

1 point system

Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

You will act as a "Full Stack" data professional, handling everything from infrastructure automation (DataOps) to complex nested data modeling. Key Responsibilities * Real-Time Ingestion: Build ...

Flight Centre Travel Group (usa) Inc

Embed DataOps practices, including pipeline observability, automated testing, CI/CD for data, and the reliability of data products * Provide technical design and best-practice guidance for data, AI ...

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Dataops information

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How much do dataops jobs pay per hour?

As of Jun 24, 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 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 jobs in the US pay 300,000 a year?

In the US, senior DataOps roles such as Lead Data Engineer or Director of Data Engineering can reach or exceed a $300,000 annual salary, especially with extensive experience, advanced skills in cloud platforms, automation, and data pipeline management. High compensation is often associated with leadership positions, specialized expertise, and working in large organizations or tech companies.

Is DataOps a good career?

DataOps is a growing field focused on streamlining data management and automation using tools like CI/CD pipelines and cloud platforms. It offers opportunities for professionals with skills in data engineering, scripting, and analytics, and typically involves collaborative work in fast-paced environments. The role can be rewarding for those interested in data workflows and continuous improvement processes.

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 jobs pay 500,000 a year in the US?

High-paying roles such as senior executives, specialized surgeons, and successful entrepreneurs can earn $500,000 or more annually. In the tech industry, senior data professionals like DataOps engineers with extensive experience, advanced skills in automation and cloud platforms, and leadership responsibilities may also reach this income level, especially in large organizations or consulting firms. Achieving this salary typically requires significant expertise, certifications, and years of experience.

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.

What jobs pay 200,000 a year in the USA?

DataOps professionals with extensive experience, advanced skills in data management, automation, and cloud platforms can earn salaries approaching or exceeding $200,000 annually, especially in senior or specialized roles. High-paying positions often require certifications, strong technical expertise, and leadership responsibilities within data engineering or analytics teams.

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 June 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.
Data Ops Lead

Data Ops Lead

Patterson-UTI

Houston, TX • On-site

Full-time

Posted 9 days ago

Patterson-UTI rating

4.4

Company rating: 4.4 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

71st of 74 rated oil and gas companies

Job description


Brief Description:
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, platform operations, and reliability, supporting critical data pipelines that power analytics, reporting, and operational decision-making across oilfield and energy operations.
The DataOps Lead will be responsible for ensuring that data is available, accurate, timely, and trustworthy, while leading operational best practices across ingestion, processing, and delivery systems running primarily on Google Cloud Platform (GCP).
This is a hands-on technical leadership role with strong expectations for ownership, cross-team collaboration, and continuous improvement.
Detailed Description:
  • Data Platform Operations
    • Own the day-to-day operational health of cloud-based data pipelines and platforms
    • Ensure high data availability, freshness, accuracy, and completeness
    • Lead operational support for batch and streaming data workloads
  • Data Reliability & Quality
    • Define and manage data SLAs, SLOs, and reliability metrics
    • Implement and maintain data quality checks, validations, and monitoring
    • Design processes for backfills, reprocessing, and failure recovery
  • Cloud & Infrastructure
    • Operate and optimize GCP-based data services, including BigQuery, Cloud Storage, Pub/Sub, and GKE
    • Partner with platform and SRE teams on scalability, performance, and cost optimization
    • Manage data infrastructure using Infrastructure as Code (Terraform)
  • Automation & Tooling
    • Build and maintain Python-based automation for data operations and monitoring
    • Improve reliability and repeatability through standardized tooling and workflows
    • Support and enhance data orchestration platforms (e.g., Airflow / Cloud Composer)
  • Incident Response & Operational Excellence
    • Lead response to data incidents, including triage, mitigation, and root cause analysis
    • Drive post-incident reviews and track corrective actions
    • Create and maintain runbooks, operational documentation, and playbooks
  • CI/CD & Governance
    • Implement CI/CD best practices for data pipelines
    • Promote testing, version control, and deployment standards across data workflows
    • Ensure data platforms align with security, governance, and access control requirements
  • Leadership & Collaboration
    • Act as a technical leader within the DataOps function
    • Partner closely with:
      • Data engineering teams
      • SRE / platform engineering
      • Analytics and business stakeholders
    • Mentor engineers and help raise the operational maturity of the data organization

Required Knowledge, Skills, and Abilities:
  • 7+ years experience in Data Engineering, DataOps, or Data Platform Operations
  • 3+ years experience operating cloud-based data platforms in production
  • Strong hands-on experience with Google Cloud Platform, including:
  • GCP: GKE, Compute Engine, Cloud Storage, Pub/Sub (or equivalents)
  • Cloud Monitoring & Logging
  • BigQuery
  • Dataflow
  • Datastream
  • IAM and networking
  • Composer/AIrflow
  • Kubernetes: deployment, scaling, reliability patterns
  • Observability: GCP Cloud Monitoring, Logging
  • Strong proficiency in Python for data pipelines, automation, and operational tooling
  • Experience with data orchestration frameworks (Airflow preferred)
  • Experience with Infrastructure as Code (Terraform)
  • Experience with Azure Devops
  • Proven experience leading data incident response and operational improvements
  • Strong SQL skills for data analysis and troubleshooting

Minimum Qualifications:
  • Bachelor's degree in Business, Information Technology, Computer Science, or a related field.
  • 7+ years experience in Data Engineering, DataOps, or Data Platform Operations
  • 3+ years leading or owning production data platforms in a cloud environment
  • Demonstrated technical leadership of data operations initiatives or teams
  • Ability to understand and speak English at a level of proficiency allowing employee to issue, receive and respond to both safety and operations-related directions in English

Preferred Qualifications:
  • Oil and Gas Industry knowledge
  • Technology/Digital Industry knowledge

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About Us
The Evolving Oil Field Demands Evolving Service Providers
NexTier is a leading provider of integrated completions that employs sustainable practices and equipment to support our customers' ESG goals while accelerating production in the most demanding US land basins.
Patterson-UTI is committed to a workplace free from discrimination and harassment, offering equal employment opportunities to all individuals regardless of personal characteristics protected by law. Employees are encouraged to report any concerns through multiple channels.

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