1

Mlops Data Engineer Jobs (NOW HIRING)

Data Engineer, OIS/CXI Analytics

Austin, TX

$113K - $136K/yr

You will contribute to MLOps data practices - including data versioning, pipeline monitoring, and model retraining data support - and help establish engineering best practices within the team. You ...

Data Engineer, OIS/CXI Analytics

Austin, TX

$113K - $136K/yr

You will contribute to MLOps data practices - including data versioning, pipeline monitoring, and model retraining data support - and help establish engineering best practices within the team. You ...

Data Engineer

Princeton, NJ · On-site

$100K - $120K/yr

Data Engineer CURE Auto Insurance is a leading direct writer of auto insurance in New Jersey ... Exposure to MLOps/data needs for fraud detection, pricing, or claims severity models is a plus.

Data Engineer

Manhattan, NY · Remote

$105K - $115K/yr

MLOps Integration: Collaborate with Data Scientists to implement automated CI/CD pipelines for ... ML Engineering: Familiarity with ML frameworks (PyTorch, TensorFlow) and MLOps tools (MLflow ...

Data Engineer

Suitland, MD · On-site

$123K - $148K/yr

Data Engineer We are looking for a skilled and passionate Data Engineer to join our team. You will ... ML Integration / MLOps : Support the implementation, deployment, and scaling of machine learning ...

Data Engineer

Newington, CT · On-site

$114K - $136K/yr

In alignment with current industrys best practices, this role integrates advanced data engineering, software development, and machine learning operations (MLOps) to deliver secure, scalable, and high ...

Data Engineer

Newington, CT

$114K - $137K/yr

In alignment with current industry?s best practices, this role integrates advanced data engineering, software development, and machine learning operations (MLOps) to deliver secure, scalable, and ...

Data Engineer

Jersey City, NJ · Hybrid

$119K - $143K/yr

Data Engineer Location : Berkeley heights NJ and Alpharetta GA , This team will be working on a ... MLOps pipelines (deployment, monitoring, lifecycle) Our environment is AWS-centric, and relevant ...

next page

Showing results 1-20

Mlops Data Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do mlops data engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for mlops data 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 the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

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

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps Data Engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What are MLOps Data Engineers?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.
More about Mlops Data Engineer jobs
What cities are hiring for Mlops Data Engineer jobs? Cities with the most Mlops Data Engineer job openings:
What states have the most Mlops Data Engineer jobs? States with the most job openings for Mlops Data Engineer jobs include:
Data Engineer, OIS/CXI Analytics

Data Engineer, OIS/CXI Analytics

Amazon

Austin, TX

$113K - $136K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,843 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Join the OIS/CXI Analytics team to build strategic data infrastructure powering Amazon's Operations Technology ecosystem. Our team provides critical data infrastructure support for OpsTech IT, supporting Amazon's global customer commitment. You'll work at the intersection of large-scale data processing and real-world operational impact - creating intelligence that directly influences how Amazon fulfills millions of orders across fulfillment centers, Amazon Fresh, Prime Now, Lockers, Pantry, and Amazon Campus.


As a Data Engineer, you will build and maintain scalable data pipelines and ML-ready data infrastructure that power AI-driven operational insights and Data Science initiatives across Amazon's global fulfillment and maintenance networks. You will design and implement ETL/ELT pipelines, build feature engineering workflows, and partner with ML Engineers, Data Scientists, Applied Scientists, and BIEs to deliver data products that drive measurable business outcomes. You will contribute to MLOps data practices - including data versioning, pipeline monitoring, and model retraining data support - and help establish engineering best practices within the team.

You will support Data Science teams by building curated, analysis-ready models and datasets and enabling self-service data access through well-governed data infrastructure. This role directly enables the team's mission to implement GenAI solutions for automated reporting, diagnostics, and predictive and prescriptive analytics across worldwide operations.
This is a high-impact individual contributor role with significant opportunity to grow technical scope and organizational influence at the intersection of data engineering, Data Science, and AI.


Key job responsibilities
- Design, build, and maintain production-grade ETL/ELT pipelines and big data infrastructure supporting OTS operational intelligence.
- Build feature engineering workflows and ML-ready data pipelines that support Data Science experimentation and production model serving.
- Contribute to data governance and quality standards across analytical and ML data products.
- Support implementation of GenAI solutions for automated reporting, diagnostic, predictive, and prescriptive analytics.
- Build and maintain semantic layers and dashboard data models that power worldwide operations business decisions.
- Partner with Program Managers, BI teams, ML Engineers, Data Scientists, and operational stakeholders to prioritize work aligned with OTS business goals.
- Follow and contribute to best practices for data engineering, including code reviews, testing, monitoring, and documentation.
A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1

Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4.

401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you. At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Amazon logo

About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US