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Big Data Devops Engineer Jobs (NOW HIRING)

Company Description Title: Sr. Hadoop Big Data Developer Location: Herndon, VA Type: Contract to Hire Required Skills: * Strong and deep knowledge of Java application development * Hands on ...

DevOps Engineer

Herndon, VA

$54.25 - $74.25/hr

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 ...

DevOps Engineer

Herndon, VA · On-site

$54.25 - $74.25/hr

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

Creve Coeur, MO · On-site

$52.25 - $69/hr

As a big data engineer you will develop innovative software using state of the art big data ... API Development (proper microservice separation, HTTP verb usage) * DevOps - understanding of OS ...

DevOps Engineer

Herndon, VA · On-site

$54.25 - $74.25/hr

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 Developer

Signal Hill, CA · Remote

$56.50 - $73.50/hr

This global organization is expanding their data department. They want a Sr. Developer who is comfortable working with business stakeholders/users. Be responsible for helping the business users ...

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 ...

DevOps Engineer

Columbia, MD · On-site

$52.25 - $71.75/hr

... Big Data environments. The DevOps Engineer will be responsible for implementing infrastructure, automating deployment processes, and ensuring the monitoring, reliability, security, and scalability of ...

Big Data Developer

San Jose, CA · On-site

$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 ...

Senior Big Data Developer

Bristol, CT · On-site

$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 ...

Big Data Developer (Spark)

Cupertino, CA · On-site

$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 Engineer

Costa Mesa, CA · On-site

$59.75 - $79/hr

Big Data Engineer Costa Mesa , CA or PHX or Bay Area Contract Job Responsibilities 10+ years of ... Good to have DevOps experience (GIT, GitHub, Bit Bucket, GitLab, IntelliJ IDEA, PyCharm) Good to ...

Showing results 21-40

Big Data Devops Engineer information

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

As of Jul 24, 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
What job categories do people searching Big Data Devops Engineer jobs look for? The top searched job categories for Big Data Devops Engineer jobs are:
Infographic showing various Big Data Devops Engineer job openings in the United States as of July 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.
Information Technology_USA - USA_Developer

Information Technology_USA - USA_Developer

Real Soft, Inc.

Jacksonville, FL • On-site

$49 - $63.75/hr

Contractor

Posted 21 days ago


Job description

**Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES B/T UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
: -/hr
MSP Owner: Kelly Gosciminski
Location: O'Fallon, MO - onsite (LOCAL ONLY)
Duration: 6 months
skill id: 10733699
Big Data Developer with Spark Scala
"• Languages: Scala, Python (PySpark), SQL
• Big Data: Apache Spark (Core, SQL, Structured Streaming)
• Streaming: Kafka
• Ingestion / Orchestration: Apache NiFi
• Storage: Apache Ozone, Ceph, object storage concepts
• OS & Tooling: Linux, Git, CI/CD, monitoring and logging tools
"
"We are looking for a highly skilled Senior Data Engineer with deep expertise in Apache Spark, Scala, and PySpark to build and operate large scale batch and streaming data processing systems. The role has a strong emphasis on real time streaming architectures using Kafka and Spark Structured Streaming, alongside ingestion and orchestration with Apache NiFi and scalable storage using Apache Ozone and Ceph. This position is ideal for engineers who enjoy solving complex performance, scalability, latency, and reliability challenges in production data platforms.
Key Responsibilities
• Design, develop, and maintain large scale Spark applications using Scala and PySpark
• Build and operate streaming heavy data pipelines using Kafka and Spark Structured Streaming
• Implement stateful streaming patterns including windowing, watermarking, late data handling, and checkpointing
• Develop robust event replay and reprocessing workflows using Kafka offsets and partitions
• Build ingestion and routing flows using Apache NiFi, including Kafka based ingestion patterns
• Implement end to end ETL/ELT pipelines with strong emphasis on low latency, fault tolerance, and scalability
• Optimize Spark jobs through partitioning strategies, memory tuning, shuffle optimization, and efficient data formats
• Integrate Spark workloads with distributed object storage systems such as Apache Ozone and Ceph
• Ensure data quality, consistency, and auditability through validation, reconciliation, and metadata capture
• Collaborate with platform, infrastructure, and operations teams on production readiness and capacity planning
• Support production systems, including monitoring, incident analysis, and root cause resolution
• Contribute to reusable frameworks, coding standards, and engineering best practices
• Participate in architecture reviews, code reviews, and technical documentation
Required Qualifications
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
• Strong hands on experience with Apache Spark in production environments
• Advanced proficiency in Scala and PySpark
• Solid understanding of distributed systems and data processing at scale
• Strong experience with Kafka based streaming architectures
• Hands on experience with Spark Structured Streaming
• Experience building batch and real time pipelines
• Hands on experience with Apache NiFi for data ingestion and flow management
• Strong SQL skills and experience working with structured and semi structured data
• Experience working with object storage or distributed storage platforms
• Proficiency with Linux, shell scripting, and Git based version control
Preferred Qualifications
• Experience with Apache Ozone and/or Ceph as storage backends for analytics workloads
• Experience implementing exactly once / at least once streaming semantics
• Strong background in Spark performance tuning (CPU, memory, I/O, shuffle)
• Experience supporting mission critical production systems with strict SLAs
• Familiarity with CI/CD pipelines and automated testing for data applications
Experience designing observability for streaming systems (lag, throughput, backpressure)"
"• Languages: Scala, Python (PySpark), SQL
• Big Data: Apache Spark (Core, SQL, Structured Streaming)
• Streaming: Kafka
• Ingestion / Orchestration: Apache NiFi
• Storage: Apache Ozone, Ceph, object storage concepts
• OS & Tooling: Linux, Git, CI/CD, monitoring and logging tools
• Apache Airflow, Apache NiFi.
Programming: Java (Core), Python (for Airflow), Unix Shell Scripting.
• Big Data/Storage: Apache Spark"
Role Descriptions: Big Data Developer
Essential Skills: Big Data Developer
Desirable Skills:
Keyword: ~Big Data Developer~
Skills: Digital : BigData and Hadoop Ecosystems~AWS DevOps and Automation
Experience Required: 6-8, Project Code :