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Mlops Data Engineer Jobs in Seattle, WA (NOW HIRING)

Staffingine LLC

Data Engineer

Redmond, WA · On-site

$128K - $154K/yr

Exposure to DataOps or MLOps practices is a plus. * Azure Data Engineer or related Microsoft certification preferred.

Zortech Solutions

MLOps Engineer

Bellevue, WA · Remote

Overall, 8-10 years of solid experience in the areas of data engineering / machine learning / data ... to-End MLOps architecture, with practical expertise in Databricks Unity Catalog, MosaicAI ...

LVT

Staff Data Engineer

Seattle, WA · On-site

You will partner closely with AI/ML research, the ML platform / MLOps function. You own the data ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...

LVT

Staff Data Engineer

Seattle, WA

$130K - $156K/yr

You will partner closely with AI/ML research, the ML platform / MLOps function. You own the data ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...

LVT

Staff Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

You will partner closely with AI/ML research, the ML platform / MLOps function. You own the data ... Set the data-engineering standards for the flywheel schema conventions, dataset contracts, quality ...

Nvidia

Senior MLOps Engineer - DSX Enablement

Seattle, WA · On-site

$130K - $178K/yr

... data engineering, or ML engineering, ideally targeting largescale production systems ... Familiarity with MLOps practices in a cloudnative context: containerization, CI/CD pipelines ...

Nametag

Senior Software Engineer, Reliability

Seattle, WA · Remote

$120K - $190K/yr

Senior Software Engineer, Reliability Remote, US About Nametag Nametag is building the future of ... MLOps & Data Pipelines: Prior experience shipping ML infrastructure into production, not just ...

Deloitte

AI Engineer Consultant

Seattle, WA · Hybrid

... and HR data domains. * 2+ years of experience operationalizing LLMOps/MLOps capabilities ... We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ...

Armaninollp

Data & AI Platform Engineer

Bellevue, WA

$129K - $155K/yr

This is an early-career engineering role focused on building, operating, and improving cloud data ... MLOps). "Armanino" is the brand name under which Armanino LLP and Armanino Advisory LLC ...

Deloitte

Lead Forward Deployed Engineer - AWS

Seattle, WA · On-site

$116K - $153K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Deloitte

Senior Forward Deployed Engineer- AWS

Seattle, WA · On-site

$118K - $163K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Microsoft

Senior Software Engineer

Redmond, WA · On-site

$137K - $180K/yr

As an AI Engineer, you will bridge the gap between AI research and real-world applications ... Data, MLOps & Productionization * Build and operate scalable data pipelines, ETL workflows, and ...

Deloitte

Forward Deployed Engineer- AWS

Seattle, WA · On-site

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

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All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Seattle, WA

Mlops Data Engineer information

See Seattle, WA salary details

$50.6K

$147.6K

$202K

How much do mlops data engineer jobs pay per year?

As of Aug 25, 2026, the average yearly pay for mlops data engineer in Seattle, WA is $147,621.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,300.00 and $156,500.00 per year, depending on experience, location, and employer.

What is an MLOps data engineer?

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.

What are the key skills and qualifications needed to thrive as an MLOps data engineer?

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 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.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

What are popular job titles related to Mlops Data Engineer jobs in Seattle, WA?

For Mlops Data Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Mlops Data Engineer jobs in Seattle, WA look for?

The top searched job categories for Mlops Data Engineer jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Mlops Data Engineer jobs?

Cities near Seattle, WA with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, and 4% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $147,621 per year, or $71 per hour.

Data Engineer

Redmond, WA • On-site

Staffingine LLC
Recruiting and Staffing Services • 51 - 200 employees
Learn more about Staffingine LLCexternal

$128K - $154K/yr

Contractor

Re-posted 29 days ago

Job description

Job Title: Data Engineer 
Job Location: Redmond WA  
Job Type: Contract 

Job Description:  

  • Design, develop, and maintain scalable data pipelines using Azure Data Factory, PySpark, and Databricks. 

  • Work with large-scale data lake and data warehouse solutions using Azure Synapse Analytics and Microsoft Fabric. 

  • Develop and optimize SQL queries, stored procedures, and ETL workflows for performance and reliability. 

  • Integrate data from multiple sources and ensure data quality, consistency, and accuracy across systems. 

  • Collaborate with business analysts and BI teams to support reporting needs, including DAX queries, tabular models, and data cubes in Power BI or Analysis Services. 

  • Contribute to architecture discussions and recommend best practices for data management, governance, and security. 

  • Troubleshoot data issues and optimize performance across data layers. 

Required Skills & Experience: 

  • 6+ years of experience in Data Engineering or related roles. 

  • Strong proficiency in SQL (complex queries, tuning, and optimization). 

  • Hands-on experience with PySpark for data transformation and processing. 

  • Proven experience with Azure Data Factory, Azure Data Lake, Azure Databricks, Synapse Analytics, and Microsoft Fabric. 

  • Experience building data models, tabular models, and writing DAX queries. 

  • Solid understanding of ETL/ELT design, data warehousing concepts, and modern data architecture. 

  • Strong analytical and problem-solving skills with attention to detail. 

  • Excellent communication and collaboration skills. 

  • Must be local to Washington State and available to work in a hybrid environment. 

Preferred Qualifications: 

  • Experience with Power BI or Azure Analysis Services. 

  • Familiarity with CI/CD pipelines and version control (Git). 

  • Exposure to DataOps or MLOps practices is a plus. 

  • Azure Data Engineer or related Microsoft certification preferred.