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Mlops Data Engineer Jobs in Virginia (NOW HIRING)

Data Engineer

Chantilly, VA ยท On-site

$110 - $170/hr

Understanding of machine learning workflows and MLOps concepts. * Experience integrating and ... This is an opportunity to work alongside highly skilled engineers, analysts, and data scientists ...

Data Engineer

Chantilly, VA ยท On-site

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology and collection methodologies means that ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology and collection methodologies means that ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$62K - $141K/yr

R0247564 Data Engineer The Opportunity: Ever-expanding technology and collection met hodologies ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$77K - $176K/yr

R0239070 Data Engineer The Opportunity: Ever-expanding technology and collection methodologies ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$62K - $141K/yr

As a data engineer, you know that organizing big data can yield pivotal insights when it's gathered ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$77K - $176K/yr

Data Engineer The Opportunity: Ever-expanding technology and collection methodologies means that ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$62K - $141K/yr

Aurora, Colorado, USA Data Engineer The Opportunity: Ever-expanding technology and collection ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$77K - $176K/yr

Data Engineer The Opportunity: Ever-expanding technology and collection methodologies means that ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology and collection methodologies means that ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$62K - $141K/yr

R0246480 Data Engineer The Opportunity: Ever-expanding technology and collection methodologies ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$62K - $141K/yr

Data Engineer The Opportunity: Ever-expanding technology and collection methodologies means that ... Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem * Top Secret clearance

Data Engineer

Chantilly, VA ยท On-site

$117K - $140K/yr

Client is seeking a data engineer to grow our team performing cutting edge client work in mission ... Understanding of machine learning workflows and MLOps concepts. Working at Edgesource: As an ISO ...

Data Engineer

Centreville, VA ยท Hybrid

$113K - $136K/yr

Client is seeking a data engineer to grow our team performing cutting edge client work in mission ... Understanding of machine learning workflows and MLOps concepts. Working at Edgesource: As an ISO ...

Data Engineer

Centreville, VA ยท On-site +1

$113K - $136K/yr

Client is seeking a data engineer to grow our team performing cutting edge client work in mission ... Understanding of machine learning workflows and MLOps concepts. Working at Edgesource: As an ISO ...

Data Engineer

Falls Church, VA ยท On-site

$150 - $175/hr

Data Engineer Location: Camp Smith, HI Clearance Level: Top Secret, Must Have Clearance to Start ... Familiarity with MLOps, API development, and secure cloud-based environments (e.g., AWS, Azure ...

Data Engineer

Chantilly, VA ยท On-site

$117K - $140K/yr

Client is seeking a data engineer to grow our team performing cutting edge client work in mission ... Understanding of machine learning workflows and MLOps concepts. Working at Edgesource: As an ISO ...

Data Engineer

Springfield, VA ยท On-site

$60K - $180K/yr

M9 Solutions is seeking a Data Engineer to work onsite in support of a government contract for a ... Familiarity with MLOps tools or platforms (e.g., SageMaker, MLflow). GH 932 Full-Time Employee ...

Senior Google AI Engineer

Mclean, VA ยท On-site +1

$105K - $145K/yr

The ideal candidate combines deep GCP/Looker/BigQuery/Vertex AI expertise with strong MLOps, data engineering fluency, and experience delivering in regulated environments. Responsibilities include ...

Showing results 21-40

Mlops Data Engineer information

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 Virginia?

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

What cities in Virginia are hiring for Mlops Data Engineer jobs?

Cities in Virginia with the most Mlops Data Engineer job openings:

Infographic showing various Mlops Data Engineer job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Data Engineer

Staffed4U

Chantilly, VA โ€ข On-site

$110 - $170/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 21 days ago


Job description

Location: Chantilly, VA
Work Schedule: Full-Time, Onsite
Clearance Required: Active TS/SCI with Full Scope Polygraph (FSP)
Employment Type: W-2

Position Overview

We are seeking a talented and mission-focused Data Engineer to join our growing team supporting cutting-edge intelligence community initiatives in Chantilly, VA. This role offers the opportunity to work with large-scale datasets and contribute to the development of a custom enterprise platform supporting critical mission objectives.

The selected candidate will play a key role in designing, building, and optimizing scalable data pipelines and architectures that support analytics, machine learning, and enterprise data integration efforts. This position is funded for an initial 9โ€“12 month period aligned with defined mission deliverables and system development timelines, with all development performed onsite at the customer location.

Key Responsibilities
  • Design, develop, and maintain ETL/ELT pipelines for both batch and real-time data processing using Python and SQL.
  • Integrate data from a variety of structured and unstructured sources, including databases, APIs, streaming platforms, PDFs, and Microsoft Office files.
  • Build scalable and maintainable data architectures to support analytics and machine learning workloads.
  • Optimize data processing workflows and queries for performance, scalability, and cost efficiency within AWS environments.
  • Support future pipeline scalability through exposure to PySpark and other distributed data processing frameworks.
  • Develop and maintain web scraping and data ingestion workflows to collect and process open-source data.
  • Transform collected information into structured datasets and visualizations for stakeholder analysis and decision-making.
Data Management & Optimization
  • Collect, clean, validate, and manage large volumes of structured and unstructured data.
  • Implement data quality controls, validation procedures, and version management practices.
  • Design and optimize data storage solutions utilizing AWS S3 for raw, intermediate, and production datasets.
  • Implement data governance best practices including documentation, cataloging, lineage tracking, and security controls.
  • Ensure compliance with customer and security requirements for data management and handling.
  • Partner closely with Data Scientists, Analysts, and Engineering teams to understand business and mission requirements.
  • Prepare clean, structured, and feature-ready datasets for analytics and machine learning applications.
  • Support feature engineering, aggregation, and large-scale data transformations.
  • Assist with deploying machine learning models into production environments while supporting monitoring, versioning, and performance optimization.
  • Integrate and consume REST APIs to support data acquisition and application workflows.
  • Utilize Docker, Kubernetes, Git, and CI/CD pipelines to support deployment and operational workflows.
Documentation & Communication
  • Document data pipelines, architectures, schemas, and transformation processes.
  • Communicate technical concepts effectively to both technical and non-technical stakeholders.
  • Participate in code reviews and promote engineering best practices across the team.
  • Contribute to continuous improvement efforts related to data engineering, automation, and platform development.
Required Qualifications Experience
  • 3โ€“5+ years of professional experience in Data Engineering or a related technical field.
  • Experience designing and implementing ETL/ELT pipelines.
  • Experience processing and managing large-scale structured and unstructured datasets.
  • Experience working in cloud-based data environments.
Technical Skills
  • Strong proficiency with Python and SQL.
  • Experience with PySpark or other distributed processing frameworks (highly desired).
  • Experience with ElasticSearch/OpenSearch technologies.
  • Experience working within AWS cloud environments.
  • Experience supporting Linux-based systems.
  • Proficiency with Git for version control and collaborative development.
  • Understanding of machine learning workflows and MLOps concepts.
  • Experience integrating and consuming REST APIs.
  • Familiarity with Docker, Kubernetes, and CI/CD pipelines.
Clearance Requirements
  • Active TS/SCI with Full Scope Polygraph (FSP) is required.
Professional Skills
  • Strong collaboration and communication skills.
  • Ability to communicate complex technical concepts to non-technical audiences.
  • Detail-oriented with a strong commitment to data quality and integrity.
  • Ability to manage multiple priorities in a fast-paced mission environment.
  • Strong analytical and problem-solving capabilities.
Desired Qualifications
  • Hands-on experience with graph databases.
  • Experience modeling, querying, and optimizing Neo4j databases.
  • Experience supporting advanced analytics, knowledge graphs, or entity resolution systems.
  • Experience working within Intelligence Community environments.
Why Join Us?

This is an opportunity to work alongside highly skilled engineers, analysts, and data scientists supporting critical national security missions. You'll have the chance to build scalable data solutions, support advanced analytics initiatives, and help shape the future of enterprise data systems in a dynamic and impactful environment.

  • Competitive Compensation
  • Comprehensive Medical, Dental, and Vision Coverage
  • 401(k) with Company Contribution
  • Paid Time Off and Company Holidays
  • Life and Disability Insurance
  • Professional Development Opportunities
  • Challenging and Meaningful Mission-Focused Work
Equal Opportunity Employer

We are committed to fostering an inclusive workplace and welcome qualified applicants from all backgrounds. Employment decisions are made without regard to race, color, religion, sex, national origin, disability, veteran status, or any other protected characteristic.

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