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Data Ops Manager Jobs in Virginia (NOW HIRING)

Guru Schools

Data/ML Ops Engineer

Mclean, VA · On-site

Data/ML Ops Engineer Position Responsibilities Summary We are looking for a Data / ML Ops ... Configure and manage vector databases and embeddings. * Collaborate with AI engineer to integrate ...

Veredus - DC

Network Operations Manager

Arlington, VA

$115K - $140K/yr

Looking for a Technical leader who will be responsible for managing the networks and data center operations. Overseeing 8 total, the Network Ops Manager mus be able to mentor, train, lead/develop.

Walmart

(USA) Coach/Ops Mgr Trainee

Norfolk, VA

... managing and supporting customer service initiatives for example store of the community and ... data insights and analysis balances short and longterm priorities and considers our customers ...

Walmart

(USA) Coach/Ops Mgr Trainee

Norfolk, VA · On-site

... managing and supporting customer service initiatives for example store of the community and ... data insights and analysis balances short and longterm priorities and considers our customers ...

Walmart

(USA) Coach/Ops Mgr Trainee

Stafford, VA

$31.25 - $38.46/hr

... managing and supporting customer service initiatives for example store of the community and ... data insights and analysis balances short and longterm priorities and considers our customers ...

Walmart

(USA) Coach/Ops Mgr Trainee

Norfolk, VA

$31.25 - $38.46/hr

... managing and supporting customer service initiatives for example store of the community and ... data insights and analysis balances short and longterm priorities and considers our customers ...

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Data Ops Manager information

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

To excel as a Data Ops Manager, you need a deep understanding of data management, analytics workflows, and process automation, often supported by a degree in computer science or a related field. Familiarity with tools like SQL, Python, cloud platforms (AWS, Azure), and orchestration systems such as Apache Airflow is typically required, along with certifications in data management or cloud services. Strong leadership, problem-solving, and communication skills help coordinate cross-functional teams and drive data initiatives. These competencies are crucial for ensuring data reliability, optimizing data pipelines, and enabling data-driven decision-making across the organization.

What are some common challenges faced by Data Ops Managers, and how can they be addressed?

Data Ops Managers often encounter challenges such as coordinating across multiple teams, ensuring data quality, and managing fast-evolving data pipelines. Success in this role requires strong communication skills to align stakeholders, robust processes for monitoring data workflows, and the ability to quickly troubleshoot issues when data delivery is disrupted. Adopting automation tools and fostering a culture of continuous improvement can help Data Ops Managers maintain reliable, scalable systems while supporting organizational data needs.

What are Data Ops Managers?

Data Ops Managers are professionals responsible for overseeing the processes, tools, and teams involved in managing and optimizing data operations within an organization. They ensure the smooth flow, quality, and accessibility of data across various platforms and departments. Their role often includes automating data pipelines, implementing data governance practices, and collaborating with data engineers, analysts, and business stakeholders to support data-driven decision making.

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

AspectData Ops ManagerData Engineer
Primary FocusOversees data operations, workflows, and process optimizationBuilds, constructs, and maintains data pipelines and infrastructure
Required SkillsData management, process improvement, team coordinationProgramming, database systems, ETL development
CertificationsData management, cloud certifications often preferredSQL, cloud platform certifications, programming languages
Work EnvironmentCollaborates with data teams, operations, and business unitsWorks closely with data scientists, analysts, and developers

While both roles involve working with data, the Data Ops Manager focuses on managing data workflows and operational efficiency, whereas the Data Engineer concentrates on building and maintaining data infrastructure. Understanding these differences helps in choosing the right career path or hiring the appropriate professional for your data needs.

What are popular job titles related to Data Ops Manager jobs in Virginia? For Data Ops Manager jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Data Ops Manager jobs in Virginia look for? The top searched job categories for Data Ops Manager jobs in Virginia are:
What cities in Virginia are hiring for Data Ops Manager jobs? Cities in Virginia with the most Data Ops Manager job openings:
Data Ops Manager jobs near you
Infographic showing various Data Ops Manager job openings in Virginia as of May 2026, with employment types broken down into 1% As Needed, 92% Full Time, 4% Part Time, 1% Temporary, and 2% Contract. Highlights an 61% Physical, 6% Hybrid, and 33% Remote job distribution.

Data/ML Ops Engineer

Guru Schools

Mclean, VA • On-site

Full-time

Posted 19 days ago

Job description

Overview:
Position Title* Data/ML Ops Engineer Position Responsibilities Summary
We are looking for a Data / ML Ops Specialist to support the data preparation and AI workflow integration for Clients Product. This role will ensure that AI pipelines are performant, secure, and ready for demo during the validation phase.
Key Responsibilities
  • Prepare structured and unstructured data for RAG pipelines.
  • Configure and manage vector databases and embeddings.
  • Collaborate with AI engineer to integrate data into demo workflows.
  • Ensure pipeline reliability, reproducibility, and observability.
  • Support versioning, experimentation, and deployment infrastructure.
Requirements
  • 3-5 years of experience in ML Ops, Data Engineering, or AI pipeline operations.
  • Familiarity with LLM tuning, prompt engineering, or semantic search.
  • Experience with cloud platforms (AWS/GCP/Azure).
  • Understanding of security and privacy in AI data pipelines.
  • Comfortable working on short-term, high-impact innovation sprints.
  • Experience working in agile environments.

Experience with the following Technologies:
  • AWS Bedrock, Anthropic Claude models (Claude Sonnet 4.5, Claude Haiku 4.5, Claude Opus 4.5)
  • PostgreSQL (RDS), AWS S3 (versioned, encrypted)
  • AWS (ECS Fargate, Lambda, EventBridge), Terraform, Docker
  • Prometheus, CloudWatch Logs/Metrics/Alarms, structured JSON logging
  • AWS KMS, Secrets Manager, IAM role-based access
  • Compliance: NIST 800-53, FedRAMP, SOC 2, PCI DSS

Skills:
Data / ML Ops AWS Bedrock, Anthropic Claude models,PostgreSQL (RDS), AWS S3,AWS (ECS Fargate, Lambda, EventBridge), Terraform, Docker

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