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Data Devops Jobs (NOW HIRING)

Kai Cyber, Inc.

DevOps Engineer - Networking

San Jose, CA

$61.75 - $84.75/hr

Design, deploy, and operate scalable data platforms and pipelines, primarily on Azure (Databricks ... DevOps/GitHub Actions * Automate infrastructure using Infrastructure as Code (Terraform) and manage ...

Kai Cyber, Inc.

DevOps Engineer - Networking

San Jose, CA · On-site

$61.75 - $84.75/hr

Design, deploy, and operate scalable data platforms and pipelines, primarily on Azure (Databricks ... DevOps/GitHub Actions * Automate infrastructure using Infrastructure as Code (Terraform) and manage ...

Software Technology Inc

Data Developer

Littleton, CO

Data Developer The Data Developer works within the ETL and Operations team to build high quality data pipelines driving analytic solutions from diverse, disparate sources of data. This role requires ...

InterSources

Sr DevOps Engineer

Irving, TX

$50.75 - $69.50/hr

Some exp from Data engineer exp. An Analytics platform engineer supporting Azure Synapse and Azure Data Factory from a DevOps perspective requires a hybrid skill set spanning primarily cloud ...

EPSoft Technologies

Devops Engineer

Plano, TX · On-site

$50.50 - $69.25/hr

Plano, TX Onsite role Bachelor's or master's degree in computer science, Information Systems, or related field * 8+ years of experience in DevOps, with at least 3 years working with cloud data ...

Monogram Health

DevOps Engineer

Brentwood, TN · On-site

$50 - $68.25/hr

They are seeking a DevOps Engineer to develop and maintain CI/CD pipelines, automate job runs, and collaborate with engineering teams to enhance their data platform. Responsibilities : • Develop ...

Artech

Cloud Data Developer/Engineer

Nutley, NJ · Hybrid

$116.40K - $139.80K/yr

Experience with CI/CD and orchestration tools such as GitHub, Azure DevOps, and Apache Airflow. Working knowledge of data science and machine learning concepts (e.g., scikit-learn, TensorFlow ...

Lancesoft

Cloud Data Developer/Engineer

Nutley, NJ · On-site

$60 - $70/hr

... DevOps, and Apache Airflow. Working knowledge of data science and machine learning concepts (e.G ... scikit-learn, TensorFlow, PyTorch). Experience with Databricks, including cluster usage and ...

Artech

DevOps Contractor

Saint Louis, MO

$51.25 - $70.25/hr

Job Title: DevOps / Platform Administration Engineer Job ID: DLTJP00051675 Location: St. Louis, MO ... The role focuses on designing, deploying, securing, and operating scalable infrastructure and data ...

Mothership

Devops Engineer

San Antonio, TX

$48 - $65.75/hr

Understanding of Apache Flink for real-time stream processing and batch data processing ... * DevOps & Automation: * Strong experience in automating deployments and infrastructure ...

Delta System and Software Inc.

DevOps Engineer

Iselin, NJ · On-site

$53.50 - $73.25/hr

Title - Senior DevOps Engineer Location - Iselin, NJ (3 days onsite, Hybrid) Looking for strong ... Develop and manage Databricks environments for data processing and analytics. * Implement ETL ...

Flexton

PPL-Advanced Data Engineer - DevOps

Cincinnati, OH

$50.75 - $69.50/hr

... - DevOps Location - Cincinnati Requirements: • Experience in Data modeling and advanced SQL techniques • Experience working on cloud migration methodologies and processes including tools like ...

Okta

Staff DevOps Data Engineer

Washington, DC · On-site

$59.75 - $81.75/hr

The Staff DevOps Data Engineer Opportunity Okta's Enterprise Data Platform and Engineering team builds the platforms and capabilities that power decision-making across the entire organization. As a ...

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How much do data devops jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for data devops in the United States is $60.53, according to ZipRecruiter salary data. Most workers in this role earn between $50.72 and $69.47 per hour, depending on experience, location, and employer.

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

To thrive as a Data DevOps professional, you need a solid background in data engineering, automation, and cloud infrastructure, often supported by a degree in computer science or a related field. Familiarity with tools like Jenkins, Docker, Kubernetes, Terraform, and cloud platforms such as AWS, Azure, or GCP is typically required, alongside experience with CI/CD pipelines and data pipeline orchestration systems like Airflow. Strong problem-solving skills, collaboration, and effective communication help you bridge the gap between data engineering and operations teams. These skills ensure efficient, reliable, and scalable data systems that support organizational analytics and business goals.

How does a Data DevOps professional typically collaborate with data engineers and data scientists on projects?

As a Data DevOps professional, you play a crucial role in bridging the gap between data engineering, data science, and operations teams. You’ll work closely with data engineers to automate data pipelines, ensure continuous integration and deployment, and maintain robust data infrastructure. Collaboration with data scientists often involves streamlining model deployment, monitoring data workflows, and troubleshooting issues to ensure that analytical solutions can be quickly and reliably put into production. Strong communication skills and a proactive approach to problem-solving are key for fostering effective teamwork across these disciplines.

What are Data DevOps professionals?

Data DevOps professionals are specialists who bridge the gap between data engineering and DevOps practices. They focus on automating, optimizing, and managing data pipelines, infrastructure, and workflows to ensure reliable and scalable data delivery. Their responsibilities often include integrating data tools with CI/CD processes, maintaining data security, and enabling collaboration between data teams and operations. By applying DevOps principles to data platforms, they help organizations deliver data-driven solutions more efficiently and with higher quality.

What is the difference between Data Devops vs Data Engineer?

AspectData DevopsData Engineer
CredentialsCertifications in cloud platforms, Devops tools, scriptingData management, SQL, cloud certifications
Work EnvironmentCollaborates with Devops, IT, and data teams; focuses on deployment pipelinesBuilds data pipelines, manages databases, and data architecture
Employer & Industry UsageTech companies, data-driven organizations, cloud providersFinancial, healthcare, tech industries, data-centric firms

Data Devops and Data Engineers share overlapping skills in cloud and scripting but differ in focus. Data Devops emphasizes deployment, automation, and infrastructure for data systems, while Data Engineers concentrate on building and maintaining data pipelines and storage solutions. Both roles are vital in modern data ecosystems, often collaborating to ensure efficient data workflows.

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What cities are hiring for Data Devops jobs? Cities with the most Data Devops job openings:
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What job categories do people searching Data Devops jobs look for? The top searched job categories for Data Devops jobs are:
Data Devops jobs near you
Infographic showing various Data Devops job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 38% Physical, 53% Hybrid, and 9% Remote job distribution, with an average salary of $125,908 per year, or $60.5 per hour.

DevOps Engineer - Networking

Kai Cyber, Inc.

San Jose, CA

$61.75 - $84.75/hr

Other

Posted 17 hours ago

Job description

Kai is the AI company rebuilding cybersecurity for the machine-speed era. Founded by second time founders and trusted by Fortune 500 enterprises, Kai is building a future where security has no categories, no silos, and no human speed bottlenecks. The Kai Agentic AI Platform replaces fragmented, human-limited workflows with agentic AI systems that continuously contextualize, assess, reason, and execute security work at machine speed - making human defenders, superhuman.
Why Join Kai
  • Well-funded: With $125M raised, we have the capital, runway, and resolve to rebuild cybersecurity from first principles.
  • Proven: We've earned the trust of Fortune 500 and Global 1000 companies, and we're just getting started. Their confidence in Kai reflects what we've built: an AI-powered cybersecurity platform that performs at the scale and speed the enterprise demands.
  • Experienced founders: Our founding team consists of second-time entrepreneurs, each with over 20 years of experience in the cybersecurity industry. Their proven expertise and vision drive our ambitious goals.
  • World-class leadership team: Our Heads of AI, Engineering, and Product bring extensive experience from some of the world's most influential companies, ensuring top-tier mentorship, direction, and vision.
  • Frontier AI Applied Research Team: Our researchers operate at the leading edge of agentic AI systems, translating breakthrough capabilities into real-world cybersecurity applications.
  • Generous compensation: We offer highly competitive salaries, equity options, and a supportive work environment. Your contributions will be valued and rewarded as we grow together.
Why This Role Matters
This role focuses on automating workflows, improving platform reliability, and supporting data engineering teams with efficient development and deployment practices. In a world where digital experiences shape trust and adoption, DataOps increases development productivity which directly drives product success and customer confidence.
What You'll Do
  • Design, deploy, and operate scalable data platforms and pipelines, primarily on Azure (Databricks, ADF, ADLS)
  • Build, manage, and optimize Apache Spark clusters and workloads for batch and streaming data processing across Azure and AWS environments.
  • Implement CI/CD pipelines for data engineering code, Spark jobs, and pipeline configurations using Azure DevOps/GitHub Actions
  • Automate infrastructure using Infrastructure as Code (Terraform) and manage containerized workloads with Docker and Kubernetes
  • Monitor data pipelines and platforms to ensure data reliability, quality, observability, and cost optimization across Azure and AWS data platforms.
  • Enforce security, governance, and best practices, collaborating closely with data engineers and platform teams in Azure-first, multi-cloud environments.
What We're Looking For
  • 6+ years of professional experience in data engineering, Data DevOps, or Data platform engineering roles
  • Proven experience supporting production-grade data platforms in enterprise environments
  • Proven ability to design, build, deploy, and maintain scalable data pipelines (ETL/ELT)
  • Deep understanding of Apache Spark for batch and streaming workloads
  • Experience creating, configuring, and managing Spark clusters, including performance tuning and cost optimization
  • Practical experience with at least one major cloud provider: AWS, Azure, or GCP.
  • Strong experience using Terraform for infrastructure automation.
  • Proven ability to diagnose and resolve system and infrastructure issues.
  • Bonus Skill: Experience deploying and managing Spark workloads on Azure Databricks or Azure Synapse

Work Location - San Jose, CA (5 days in the office)

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