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Mlops Data Engineer Jobs (NOW HIRING)

Data Engineer

Newington, CT · On-site

$114K - $136K/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

Dallas, TX · On-site +1

$113K - $136K/yr

Data Engineer (AI & Cloud Platforms) We are seeking a Data Engineer to support the design ... Exposure to machine learning pipelines, MLOps concepts, or AI-driven data workflows preferred

Data Engineer

Suitland, MD

$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

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

Brentwood, TN · On-site

$108K - $130K/yr

OPPORTUNITY We are seeking an experienced Data Engineer with 2-3+ years of hands-on experience to ... Machine Learning experience including model development, deployment, or MLOps practices

Data Engineer- SME

Huntsville, AL · On-site

$112K - $135K/yr

Overview SOSi is seeking an expert Data Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in ...

Data Engineer- SME

Huntsville, AL

$112K - $135K/yr

Overview SOSi is seeking an expert Data Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in ...

Senior Data Engineer

$108K - $147K/yr

Mentor AI engineers in data engineering and MLOps best practices * Mentor engineers across Keebo in data engineering and architecture best practices You Have * Experience as a data engineer, building ...

Data Engineer- SME

Huntsville, AL · On-site

$112K - $135K/yr

Overview SOSi is seeking an expert Data Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in ...

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 ...

Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

We are seeking a highly skilled Data Engineer with 10+ years of experience in designing, building ... Exposure to machine learning data pipelines and MLOps concepts. * Cloud certifications (AWS, Azure ...

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

We are seeking a highly skilled Data Software Engineer to design, develop, and maintain scalable ... MLOps) practices Experience with data visualization tools and business intelligence platforms

Data Engineer III

San Ramon, CA · On-site +1

$128K - $153K/yr

Collaborate cross-functionally with DevOps, Platform Engineering, and MLOps roles to integrate data solutions into the broader technology environment and shared AI infratstructure - Mlflow registries ...

Data Engineer III

San Ramon, CA · On-site +1

$128K - $153K/yr

Collaborate cross-functionally with DevOps, Platform Engineering, and MLOps roles to integrate data solutions into the broader technology environment and shared AI infratstructure - Mlflow registries ...

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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 Jul 11, 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.

Are MLOps engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects as organizations prioritize operationalizing AI solutions.

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.

What is the salary of data engineer in MLOps?

The salary of an MLOps Data Engineer typically ranges from $90,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning tools tend to earn higher salaries.

What engineer makes 500,000 a year?

Highly experienced senior MLOps Data Engineers with specialized skills in cloud platforms, automation, and large-scale data processing can earn salaries approaching or exceeding $500,000 annually, especially in competitive tech hubs or large organizations. Such roles often require advanced certifications, extensive experience, and expertise in tools like Kubernetes, Docker, and cloud services like AWS or Azure.

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.
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:
Infographic showing various Mlops Data Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Data Engineer

Data Engineer

PCX Aerosystems

Newington, CT • On-site

$114K - $136K/yr

Full-time

Re-posted 8 days ago


Job description

About the Organization
Applied Aerospace & Defense (Applied) is a premier provider of advanced design, engineering, and vertically integrated manufacturing solutions for leading and next-generation space and defense technology companies. Applied builds complex hardware for extreme operating environments and is focused on three core markets: Space and Launch Systems, Defense Aviation and Airborne Systems, and C5ISR and Precision Strike Systems. With decades of space and defense manufacturing heritage, Applied combines deep material science and IP-enabled process expertise with the ability to enable rapid prototyping, enhance new product development, and responsively scale production. Across its nationwide infrastructure of advanced manufacturing facilities, Applied continuously supports a balanced mix of next-generation technology and platform development, large scale production programs, and aftermarket sustainment for enduring platforms.
EOE Statement
Applied Aerospace and Defense is an equal opportunity employer.
Description
OVERVIEW OF POSITION:
The Data Engineer is a strategic technical role responsible for architecting, building, and sustaining the organization's modern data ecosystem, including cloud-based data platforms, analytics environments, and AI/ML capabilities. 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 high-performance solutions across the enterprise.
This position designs and manages end-to-end data pipelines, develops cloud-native and on-premise data architectures, and transforms raw structured and unstructured data into high-quality, trusted information assets that support decision-making and mission-critical operations. The Data Engineer also builds custom applications, automation tools, and reusable data services to streamline workflows and accelerate digital transformation efforts.
In addition, this role leads the operationalization of machine learning models, ensuring they are reproducible, observable, and deployed with robust CI/CD and MLOps practices to solve complex business and operational challenges.
Operating within the aerospace and defense sector, the Data Engineer collaborates closely with cross-functional teams to maximize data value, enhance data quality, and maintain strict compliance with Cybersecurity Maturity Model Certification (CMMC) requirements and the National Institute of Standards and Technology (NIST) Special Publication 800-171 security controls. This position does not require security clearance.
ESSENTIAL JOB FUNCTIONS:
Data Architecture and Business Intelligence
  • Design and optimize scalable SQL and Python-based data transformations, algorithms, and analytics solutions that drive operational improvements and strategic business decisions.
  • Architect, build, and maintain batch, micro-batch, and real-time data pipelines using modern ETL/ELT frameworks to integrate data from enterprise systems, cloud platforms, OT systems, and external sources.
  • Develop advanced business intelligence and reporting solutions using Power BI, SSRS, and related tooling, including semantic models, reusable datasets, and interactive dashboards.
  • Partner with cross-functional stakeholders to rapidly interpret complex requirements and translate them into scalable, high-value analytical tools, visualizations, and data products.
  • Build programmatic and data-driven solutions to enhance Operational Technology, digital manufacturing, and Industry 4.0 initiatives across the organization.
  • Implement and maintain strong data governance practices including data quality monitoring, validation rules, lineage documentation, and schema management across all enterprise data ecosystems.

Software and Automation Development
  • Develop automation solutions using scripting technologies such as PowerShell, Python, C#, and PERL to eliminate manual processes and improve system performance and reliability.
  • Maintain and enhance organizational SharePoint sites, ASP.NET Core, and PHP-based dashboards, ensuring stability, secure configuration, and alignment to evolving business operations.
  • Build and support web applications and integration services using modern frameworks including Bootstrap, HTML5, REACT.js, Node.js, ASP.NET Core, Django, PHP, or similar technologies to streamline workflows and system interoperability.
  • Utilize Microsoft Graph API to securely integrate with Microsoft 365 services, enable advanced automation, and extend enterprise collaboration tools.
  • Apply Microsoft Power Platform capabilities, including Power Apps, Power Automate, and Power BI to rapidly develop internal solutions and maximize existing technology investments.
  • Assess business requirements and recommend appropriate development frameworks, architectural patterns, and technologies to ensure scalable and maintainable custom solutions.
  • Evaluate incoming business requirements to identify and recommend the most appropriate development tools and frameworks for each custom solution.

Artificial Intelligence and Machine Learning
  • Design, develop, and deploy machine learning and artificial intelligence models tailored to complex business and operational challenges.
  • Collect, engineer, and prepare large, diverse datasets for model development, ensuring proper handling, labeling, and validation across the full lifecycle.
  • Train, test, and optimize predictive models to achieve high performance, reliability, and scalability using modern ML frameworks and MLOps best practices.
  • Integrate AI/ML models into business applications, APIs, data pipelines, and enterprise platforms to ensure seamless operationalization and measurable value.
  • Monitor, maintain, and retrain production ML models, implement continuous evaluation, drift detection, and responsible AI governance standards.

Technology Leadership and Compliance
  • Maintain and enhance existing scripted reporting and automation tools to ensure their continued alignment with evolving business and technical requirements.
  • Stay informed on emerging data engineering, analytics, AI/ML, automation, and cloud technologies, providing strategic recommendations to guide future technical investments.
  • Coordinate with enterprise architecture and follow established organizational architectures, development methodologies, and engineering standards, including code quality, secure coding practices, data modeling, design patterns, documentation requirements, and DevSecOps processes.
  • Ensure all data systems, pipelines, custom applications, and integrations operate in full compliance with CMMC and NIST SP 800-171 requirements.
  • Protect Controlled Unclassified Information (CUI) and Federal Contract Information (FCI) using securecoding practices, data governance standards, and cybersecurity-aligned handling procedures.

SKILLS • EXPERIENCE • EDUCATION:
Required Qualifications
  • Bachelor's degree in computer science, Data Engineering, Information Technology, Analytics, Data Science, or a related technical field, or an equivalent combination of education and experience.
  • Extensive experience in data engineering, data modeling, and database management using SQL across platforms such as Microsoft SQL Server, Oracle, PostgreSQL, or similar relational database systems.
  • Strong proficiency in object-oriented programming and scripting languages including Python, C#, Java, PHP, R, and familiarity with PERL (beneficial but not required).
  • Proven expertise in building business intelligence and data visualization solutions using Power BI, Tableau, Qlik, Looker, MicroStrategy, Oracle Analytics, or similar tools, SSRS, and Power Query.
  • Hands on experience developing web applications, managing SharePoint environments, and utilizing the Microsoft Power Platform.
  • Experience leveraging application programming interfaces, specifically Microsoft Graph API, for secure system integrations and workflow automations.
  • Demonstrated ability to collect, process, and analyze large datasets to support data driven business initiatives.
  • Experience with data ingestion and data integration using tools such as SQL, SSIS, Talend, Boomi, or similar ETL/ELT and integration platforms to build reliable, scalable, and automated data pipelines.
  • Superior analytical and problem-solving skills, with the ability to translate non-technical business requests into technical data solutions.
  • Excellent communication skills for collaborating with technical teams and business stakeholders.

Preferred Qualifications
  • Master's degree in data science, Computer Science, Artificial Intelligence, Analytics, Machine Learning, or closely related technical discipline.
  • Practical experience designing, training, and deploying machine learning models in a live production environment.
  • Familiarity with modern data workflow management and distributed processing technologies, including Apache Airflow, Prefect, Dagster, Apache Spark, Databricks, or equivalent cloud-native orchestration and compute frameworks.
  • Experience working within the aerospace, defense, or government contracting sectors.
  • Deep understanding of Department of Defense cybersecurity compliance requirements including CMMC, NIST SP 800 171, and ITAR regulations.
  • Certifications in Microsoft data platforms, cloud architectures, or data engineering specialties.

ADDITIONAL INFORMATION:
This job description is intended to describe the general nature and level of work being performed. It is not an exhaustive list of all responsibilities, duties, or skills required. Employees may be required to perform other job-related duties as assigned, consistent with business needs and applicable law.
This position requires no security clearance.
Due to the nature of our work and applicable U.S. export control laws, this position requires International Traffic in Arms Regulations (ITAR) eligibility. Only individuals who qualify as a U.S. person as defined by ITAR (U.S. citizens, U.S. permanent residents, refugees, or asylees), unless specified otherwise within job description, are eligible for employment.
Applied Aerospace and Defense is committed to equal employment opportunity. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, veteran or military status, or any other characteristic protected by applicable federal, state, or local law.
Applicants who require reasonable accommodation for any part of the application or hiring process due to disability, medical condition, or other protected reason may contact the Human Resources Department. Requests will be reviewed in accordance with applicable law.
Where required by law, the applicable pay range and a summary of benefits and other compensation for this position will be provided.
Position Requirements
Shift
-not applicable-
Full-Time/Part-Time
Full-Time
Location
Applied Aerospace & Defense, Newington
Category
Information Technology
Req Number
INF-26-00002
Position
Data Engineer
Close Date
Post Internal Days
0
Number of Openings
1
Exempt/Non-Exempt
Non-Exempt
Hiring Manager(s)
This position is currently accepting applications.