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Big Data Devops Engineer Jobs (NOW HIRING)

Data Bricks Devops Engineer

Dallas, TX · On-site

$52.25 - $71.50/hr

ClifyX is seeking a Data Bricks DevOps Engineer with extensive experience in API development and ... big data concepts. Company : ClifyX provides innovative business solutions which satisfy ...

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Big Data Developer

Los Angeles, CA

$57 - $74/hr

Company Description Intelliswift Software, Inc Big Data & Java experience is mandatory Experience in Big Data Tech stack - Mapr, Hive, PIG is mandatory Must have Data Management experience in large ...

Big Data Engineer

Tampa, FL · On-site

$52.75 - $69.75/hr

TOP REQUIREMENTS: Big Data (Spark, Scala, Hive, Hadoop Ecosystem) Data Streaming (Kafka ... Experience with DevOps, Continuous Integration, and Continuous Delivery. * Expertise in performance ...

Databricks Devops

Dallas, TX · On-site

$52.25 - $71.50/hr

Tata Consultancy Services is seeking a Databricks Devops Engineer. The role requires extensive ... Engineer • Strong understanding of ETL/ELT processes, data modeling, data warehousing, and big ...

Big Data Developer

San Jose, CA

$62 - $80.50/hr

Hadoop Big Data Technologies HBase Linux Core Java Mongo DB Big Data Architecture knowledge is prefered Additional Information All your information will be kept confidential according to EEO ...

Big Data Developer (Spark)

Cupertino, CA

$65.50 - $84.75/hr

Big Data Developer (Spark) Location: Cupertino, CA Duration: 6 to 12 months Interview: Phone and Skype - Spark and Scala, Java, Hadoop MR Unix, Desired years of experience* : 10- 12 years of ...

Big data Developer

Tampa, FL · On-site

$48.25 - $62.50/hr

... Big Data eco system. 5. Experience with Linux-based infrastructures. Competencies: • Strong verbal and written communication skills; ability to face off to business users • Self-motivated ...

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Software/DevOps Engineer

Annapolis, MD · On-site

$52.25 - $71.50/hr

The DevOps Engineer shall be responsible for implementing a Zero-touch provisioning (ZTP) solution ... big data such as Splunk and Elastic Stack § Experience with SQL technologies such as MySQL ...

Senior Big Data Developer

Bristol, CT

$53 - $68.75/hr

Be it core Java, full-stack Java, Web/UI designers, Big Data or Cloud or Mobility developers/architects, we have them all. Responsibilities: Design, develop and implement big data solutions on both ...

Data DevOps Engineer

Santa Clara, CA · On-site

$200K - $220K/yr

Interface with DevOps teams to build out the pipelines. * Interface with Data Scientists and ... We celebrate achievements both big and small, with regular recognition programs and awards that ...

Senior DevOps Engineer

Herndon, VA · On-site

$133K - $171K/yr

The DevOps Engineer will leverage their technical background to help deliver automation and big data analytics for the IC community. You will be trained in DevOps and work alongside a collaborative ...

Big Data Engineer

Rolling Meadows, IL

$56 - $74.25/hr

Looking for an experienced Senior Big Data Developer Experience: 8 - 10 years Job Location: Rolling Meadows, IL Requirements Primary / Essential Skills : SPARK with Scala or Python Secondary ...

Data DevOps Engineer

Santa Clara, CA · Hybrid

$200K - $220K/yr

Interface with DevOps teams to build out the pipelines. * Interface with Data Scientists and ... We celebrate achievements both big and small, with regular recognition programs and awards that ...

Big Data Developer

Chicago, IL · On-site

$54.75 - $71/hr

Job Title Onsite/hybrid***4-6 years of experience in Big Data development using Hadoop with a good understanding in all phases of software development life cycle.***Experience using Hadoop ...

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Big Data Devops Engineer information

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How much do big data devops engineer jobs pay per hour?

As of Jun 26, 2026, the average hourly pay for big data devops engineer 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 some common challenges Big Data DevOps Engineers face when managing data pipelines in a production environment?

Big Data DevOps Engineers often encounter challenges related to scaling and maintaining complex data pipelines. Ensuring high availability and fault tolerance while handling large volumes of data can be demanding, especially when integrating new tools or technologies. They must also proactively monitor system performance, quickly resolve bottlenecks, and collaborate closely with data engineering and operations teams to implement robust deployment and automation strategies. Staying up-to-date with evolving cloud and big data platforms is crucial for success in this dynamic role.

What is the difference between Big Data Devops Engineer vs Data Engineer?

AspectBig Data Devops EngineerData Engineer
Required CredentialsCertifications in cloud platforms, Linux, scriptingData management, SQL, cloud certifications
Work EnvironmentCloud platforms, automation tools, CI/CD pipelinesData warehouses, ETL processes, databases
Employer & Industry UsageTech companies, data-driven organizationsFinance, healthcare, tech sectors
Common Search & Comparison IntentUnderstanding roles in data infrastructure & automationData pipeline development & management

The Big Data Devops Engineer focuses on automating and maintaining scalable data infrastructure using DevOps practices, cloud tools, and automation. In contrast, Data Engineers primarily design, build, and manage data pipelines and storage solutions. While both roles require knowledge of cloud platforms and data management, the DevOps Engineer emphasizes deployment, automation, and system reliability, whereas Data Engineers concentrate on data architecture and processing.

What are Big Data DevOps Engineers?

Big Data DevOps Engineers are IT professionals who specialize in managing, automating, and optimizing the deployment and operation of big data platforms and applications. They work at the intersection of development (Dev) and operations (Ops) to ensure that data pipelines, processing workflows, and analytics tools are reliable, scalable, and efficient. Their responsibilities often include configuring cloud infrastructure, automating deployment processes, monitoring system health, and collaborating with data engineers and developers. By leveraging DevOps practices, they help organizations process and analyze large volumes of data more effectively and securely.

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

A Big Data DevOps Engineer needs a strong background in computer science, experience with big data platforms like Hadoop or Spark, and proficiency in scripting languages such as Python or Bash. Familiarity with CI/CD tools (e.g., Jenkins), containerization (Docker, Kubernetes), and cloud services (AWS, Azure, GCP), as well as relevant certifications, is typically required. Strong problem-solving abilities, communication skills, and a collaborative mindset help engineers efficiently bridge development and operations teams. These skills ensure the secure, scalable, and reliable deployment of big data solutions that meet business objectives.
More about Big Data Devops Engineer jobs
Infographic showing various Big Data Devops Engineer job openings in the United States as of June 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 100% In-person job distribution, with an average salary of $125,908 per year, or $60.5 per hour.
Azure Databricks DevOps Engineer (API & Platform)

Azure Databricks DevOps Engineer (API & Platform)

InterSources

Cupertino, CA • On-site

$65 - $89.25/hr

Other

Posted 4 days ago


Job description

Azure Databricks DevOps Engineer (API & Platform)

Location - SF or Cupertino, California, Dallas Texas, Hopkins, MN, Atlanta GA, Charlotte NC (Local to these location only) -- onsite Duration – 8 Months contract Role MoI- 2 Video

Job Description

  • As an Analytics platform engineer supporting Azure & AWS Databricks from a DevOps perspective requires a hybrid skill set spanning primarily cloud infrastructure management and deployment, automation and CI/CD practices and it is helpful if they a background or exposure to ELT and data engineering and Database Administration Concepts etc.
  • The resource will be responsible developing the foundation Databricks for use within client as an Analytics Platform Engineering team member where they will develop automation via terraform modules or other tooling to deploy Databricks Workspaces, along with other cloud resources, we are developing a platform ontop of a PaaS offering where you also need to implement a CICD solution in Gitlab.
  • Core Responsibilities
  • Implement CI/CD Pipelines: Design and maintain continuous integration and continuous deployment pipelines using tools like Gitlab, Azure DevOps or GitHub Actions for deploying data pipelines and infrastructure changes.
  • Infrastructure as Code (IaC): Provision and manage Azure Analytics services (Databricks, etc.) through code using tools such as Terraform, ARM templates, or Bicep to ensure consistency and repeatability.
  • Platform Operations: Deploy, manage, and optimize the performance and resource utilization of Azure data services, including monitoring and troubleshooting data pipeline failures and performance issues.
  • Automation & Scripting: Automate routine operational tasks and application deployments using scripting languages like Python, PowerShell, or Bash.
  • Security & Compliance: Implement security best practices, including identity and access management (IAM), data encryption, and compliance with data governance policies (e.g., GDPR) within the platform.
  • Collaboration: Work closely with data engineers, data scientists, and business analysts to translate data requirements into robust technical solutions and foster a DevOps culture within the organization

Key Skills and Qualifications

  • Cloud Platform Expertise: Deep knowledge of Microsoft Azure and/or AWS services, specifically, Azure and or AWS Databricks, Exposre to Azure Synapse Analytics (SQL pools, Spark pools, pipelines), Azure Data Factory (pipelines, triggers, data flows), would be beneficial as well. Azure Data Lake Storage (ADLS), and Azure Monitor

DevOps Tools & Methodologies:

  • CI/CD platforms: Expertise Gitlab or Azure Devlops (Azure Pipelines, Boards, Repos) or GitHub Actions.
  • Version Control: Strong experience with Git and branching strategies.
  • IaC tools: Proficiency in Terraform, Bicep, or ARM templates.
  • Containerization: Experience with Docker and container orchestration (Azure Kubernetes Service - AKS) is highly beneficial.
  • Programming & Scripting Languages: Proficiency in Python, SQL (SQL, query optimization), and scripting languages like PowerShell or Bash for automation and data manipulation tasks.
  • Data Engineering Fundamentals: Basic understanding of Data engineering principals such as ETL/ELT processes, data modeling, data warehousing, and big data concepts.
  • Monitoring & Logging: Experience implementing monitoring, logging, and alerting solutions using tools like Azure Monitor, Log Analytics, and Application Insights.
  • Soft Skills: Excellent problem-solving, analytical, and communication skills to work effectively in fast-paced, agile environments.
  • Preferred Certifications: Microsoft Certified: Azure Data Engineer Associate (DP-203) or Microsoft Certified: Azure DevOps Engineer Expert (AZ-400) are highly valued.

Must Have

  • 4+ years of experience developing APIs and integrating with 3rd party APIs. Strong SQL skills (SQL Server or Oracle). Familiarity with scripting languages (Python, Bash, Powershell). Experience with version control systems (Git, GitHub, GitLab). Knowledge of CI/CD pipelines and DevOps best practices. Understanding of workflow automations is a plus. Excellent problem-solving, analytical, and communication skills.
  • Azure AD, OAuth, JWT, Microsoft Teams SDK, Building apps for teams, Azure hands with AD B2C, BOT, SignalR, AKS, App Registrations, App Insights
  • Azure Databricks
  • CI/CD: Jenkins, Terraform, GitLab CI/CD
  • Terraform Module Development

Nice To Have

  • Data Engineer
  • Strong understanding of ETL/ELT processes, data modeling, data warehousing, and big data concepts.

InterSources logo

About InterSources

Sourced by ZipRecruiter

In 2007, Our journey began as pioneers in the realm of technology and security. Since then, InterSources Inc. has evolved into a trusted partner, leading the way in Cloud Security, Cybersecurity, PLG Consulting, Digital Transformation, and Professional Services. With a rich history of excellence and a forward-thinking approach, we continue to secure your digital future and drive innovation. Explore our legacy of success and discover the possibilities that lie ahead.

Company size

51 - 200 Employees

Headquarters location

Fremont, CA, US

Year founded

2007

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