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Data Ops Engineer Jobs (NOW HIRING)

Saic

Data Ops Engineer

San Diego, CA · On-site

$200 - $240/hr

Description We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a ...

SAIC

Data Ops Engineer

San Diego, CA · On-site +1

$200K - $240K/yr

ORA_ON_SITE Description We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming ...

SAIC

Data Ops Engineer

San Diego, CA · On-site

$200K - $240K/yr

ORA_ON_SITE Description We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming ...

SAIC

Data Ops Engineer

San Diego, CA · On-site

$200K - $240K/yr

Description We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a ...

Xenith Solutions

Data Ops Engineer

San Diego, CA · On-site

$121K - $146K/yr

They are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines, ensuring reliable data flow and quality while collaborating with various engineering teams.

Xenith Solutions LLC

Data Ops Engineer

San Diego, CA · On-site

$121K - $146K/yr

We are seeking a Data Operations Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a wide ...

Xenith Solutions

Data Ops Engineer

San Diego, CA · On-site

$121K - $145K/yr

We are seeking a Data Operations Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a wide ...

2K

Data Ops Engineer

Novato, CA · On-site

$62 - $84.75/hr

Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers, are the professional publishing stewards of 2K's portfolio currently includes several AAA, sports ...

2K

Data Ops Engineer

Novato, CA · On-site

$62 - $84.75/hr

Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers, are the professional publishing stewards of 2K's portfolio currently includes several AAA, sports ...

Career Site

Senior Cloud Data Ops Engineer

Quincy, MA · On-site

$140K - $180K/yr

Summary of Position: he Cloud Data Ops team is hiring a Senior Cloud DBA & Data Platform Engineer who brings deep, hands-on DBA expertise across SQL Server, Postgres (w/Timescale) and Oracle ...

Salesforce, Inc.

ES Data Ops Strategist

Indianapolis, IN · On-site

$85 - $110/hr

We are seeking a self-driven ES Data Ops Engineer & Strategist within the ES Office of Data -- to establish and scale the data foundations specifically for our HR Operations team. This is a unique ...

Noblesoft Technologies

Azure Data/Ops Architect

Dallas, TX · On-site

$62.75 - $81.75/hr

Azure Data/Ops Architect Location: Dallas TX or San Francisco CA Role/Responsibilities We are ... This role bridges data engineering, cloud architecture, and DevOps practices to ensure efficient ...

Harris Associates

Data Analyst, Data Ops

Chicago, IL · On-site

The Data Ops team is responsible for delivering scalable data, reporting and operational analytics ... Bachelor's degree in Data Analytics, Engineering, Computer Science, Business, or a related field ...

University of Florida

OPS Engineer

Gainesville, FL · On-site

$35.92 - $40.71/hr

OPS Engineer Job no: 540809 Work type: Temp Full-Time Location: Main Campus (Gainesville, FL ... Data analysis to derive meaningful insights. The engineer will collect data from experiments for ...

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Data Ops Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do data ops engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data ops engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is a Data Ops Engineer?

Data Ops Engineers are professionals who bridge the gap between data engineering and operations. They focus on automating, monitoring, and optimizing data pipelines to ensure reliable, efficient, and secure data flow within organizations. Their responsibilities often include managing data integration, workflow orchestration, deployment of data infrastructure, and implementing best practices for data quality and governance. Data Ops Engineers work closely with data scientists, analysts, and IT teams to support data-driven decision-making and maintain high data availability. Their role is crucial in modern organizations that rely on large-scale data processing and analytics.

How does a Data Ops Engineer typically collaborate with data scientists and software engineers within an organization?

Data Ops Engineers play a crucial role in bridging the gap between data science and engineering teams. They ensure smooth data pipeline operations, help automate workflows, and support data scientists by providing reliable, scalable infrastructure. Collaboration often involves participating in cross-functional meetings to understand data requirements, troubleshooting data quality issues, and implementing solutions that enable efficient experimentation and model deployment. This collaborative environment helps facilitate quick iterations and reliable delivery of data products.

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

To thrive as a Data Ops Engineer, you need a solid background in data engineering, automation, and cloud infrastructure, often supported by a degree in computer science or related field. Experience with tools like Apache Airflow, Docker, Kubernetes, CI/CD pipelines, and proficiency in scripting languages such as Python or Bash is typically required. Strong problem-solving skills, attention to detail, and effective communication help you collaborate with data teams and troubleshoot complex data workflows. These skills ensure reliable data delivery, streamlined operations, and scalable solutions that support organizational data goals.

What is the difference between Data Ops Engineer vs Data Engineer?

AspectData Ops EngineerData Engineer
CredentialsCertifications in data management, cloud platforms, scriptingCertifications in data engineering, SQL, cloud services
Work EnvironmentFocus on data pipelines, automation, deployment, and monitoringFocus on data modeling, ETL processes, database design
Industry UsageUsed in organizations emphasizing data operations, automation, and DevOps practicesUsed in data-centric roles focusing on building data infrastructure

While both roles work with data infrastructure, Data Ops Engineers primarily focus on automating and managing data pipelines and deployment processes, whereas Data Engineers concentrate on designing and building data systems. The roles often overlap but differ in their core focus areas and responsibilities.

Is data operations a good career?

Data Operations, often involving roles like Data Ops Engineer, is a growing field focused on managing data pipelines, automation, and infrastructure. It offers strong job demand, competitive salaries, and opportunities to work with tools like cloud platforms and data management systems, making it a viable career choice for those interested in data and technology.
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What states have the most Data Ops Engineer jobs?

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What job categories do people searching Data Ops Engineer jobs look for?

The top searched job categories for Data Ops Engineer jobs are:

Data Ops Engineer jobs near you
Infographic showing various Data Ops Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Ops Engineer

Saic

San Diego, CA • On-site

$200 - $240/hr

Other

Re-posted 9 days ago

SAIC rating

7.6

Company rating: 7.6 out of 10

Based on 81 frontline employees who took The Breakroom Quiz

103rd of 226 rated it services

Job description

Description

We are seeking a Data Ops Engineer to design, build, and maintain real-time data ingestion pipelines. In this role, you will be responsible for the reliable flow of streaming data from a wide range of sources into our data platform, ensuring data quality, observability, and scalability. You'll partner closely with data engineers, platform engineers, and analytics teams to deliver trustworthy, low-latency data that supports operational decisions. This position is on-site in San Diego, CA. Aid the team in delivering continual data feeds to users and monitoring the status of the health of data quality and overall data ingest.



  • Aid the team in delivering continual data feeds to users and monitoring the status of the health of data quality and overall data ingest.

  • Build resilient pipelines with appropriate backpressure, prioritization, retries, and error-handling strategies.

  • Employ a variety of data manipulation and visualization tools to effectively convey status and historical trends to leadership, users, and data team.

  • Collaborate with platform, software, and other data engineers to (re)configure data ingestion pipelines to be more reliable.

  • Work with data in a variety of formats including Excel, CSV, JSON, and XML.

  • Support the incident management process to ensure that incidents are documented and resolved quickly. Perform root cause analysis to understand and

  • prevent repeated occurrences of data outages.

  • Develop and maintain software to automate monitoring of real-time feeds and alert for timeliness, volume, lineage, and distribution data issues. Process learnings and rely on historical data from data pipelines, translating them into actionable steps to improve data ingest.

  • Partner with security and governance teams to enforce encryption, authentication authorization, and data classification.

  • Demonstrate proficiency with frequent-used scripting language (Python, bash) commonly used in data science applications and data analytics.


Qualifications

  • U.S. citizenship and an active TS/SCI

  • Bachelor of Science required in the following preferred fields: Computer Science, Mathematics, EE, Physics, Information Systems, or Information Technology.

  • 3+ years of experience in data engineering, data operations, or DevOps roles supporting production data pipelines.
    Tools

  • Apps/Platforms: NiFi, Kafka, Grafana, Prometheus, Apache Flink/Spark Streaming, Snowflake, Elasticsearch, Kafka, MQTT, JMS
    Operating Systems: Windows, Linux (RedHat).


Target salary range: $200,001 - $240,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

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