Enterprise Data Management & Virtualization Specialist chez LLNL

Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are dedicated to fostering a culture that values individuals, talents, partnerships, ideas, experiences, and different perspectives, recognizing their importance to the continued success of the Laboratory’s mission.

Pay Range

$168,780 - $214,032 annually

We're looking for an experienced Enterprise Data Management & Virtualization Specialist to enable seamless data access and delivery across our enterprise systems—specifically to empower development teams supporting Finance, HR, Procurement, and other business operations. This role will focus on enabling AI and analytics by leveraging data virtualization tools such as Denodo, ensuring consistent, governed, and real-time access to distributed data assets.

You will work at the intersection of data governance, AI enablement, and enterprise operations, partnering with application developers and business analysts to ensure the right data is available, high-quality, and ready for intelligent decision-making. The position will be in the Enterprise, Applications & Services (EAS) Division within the Computing Directorate.

This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home one or more days per week. 

You will

• Design, implement, and manage data virtualization layers using tools like Denodo to provide a unified view of enterprise data across on-prem and cloud systems.
• Collaborate with enterprise development teams to virtualize data sources relevant to Finance, HR, Procurement, Supply Chain, and other operational domains.
• Create reusable virtual data services (VDS) and semantic layers to minimize redundancy and streamline AI/ML workflows.
• Work with development teams to leverage existing enterprise data and create new data structures in a Denodo data virtualization environment.
• Work with development teams to develop and enforce data governance policies, metadata standards, and data stewardship processes across operational domains.
• Support the creation and maintenance of LLNL enterprise-wide data catalogs, lineage, and business glossaries.
• Partner with application developers to provide governed, high-quality data feeds for AI model development, training, and deployment.
• Work closely with ML engineers to ensure virtualized data sources meet performance, accuracy, and versioning requirements for real-time and batch AI use cases.
• Partner with both application development teams and their functional counterparts to translate operational data requirements into scalable, governed data assets.
• Support enterprise software and analytics development in delivering data-driven solutions for operational efficiency, forecasting, and intelligent automation.
• Perform other duties as assigned.

• Ability to obtain and maintain a U.S. DOE L-level security clearance in the future. This requires U.S. Citizenship.
• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• Significant experience in enterprise data management, data integration, or data architecture.
• Significant experience with Denodo or a comparable data virtualization platform.
• Advanced knowledge of business operations data (e.g., ERP systems like Oracle Finance, Oracle HCM Cloud, PeopleSoft, Hexagon/Infor EAM).
• Significant experience with SQL, data modeling, metadata management, and data cataloging
• Advanced experience with cloud data platforms (e.g., Snowflake, Redshift, BigQuery, Databricks) and API-based data access.
• Advanced knowledge of AI/ML pipelines, data readiness practices, and ethical data usage principles.

Desired Qualifications:

• Denodo Platform Certified Architect or Developer
• Significant Experience working within Agile/Scrum environments supporting cross-functional development teams
• Familiarity with data privacy laws, data residency, and compliance relevant to Finance, HR, and Health related data
• Exposure to AI/ML tooling ecosystems (e.g., Databricks, Azure ML, SageMaker)

#LI-Hybrid

Position Information

This is a Career Indefinite position, open to Lab employees and external candidates.

Why Lawrence Livermore National Laboratory?

• Included in 2025 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Our values - visit https://www.llnl.gov/inclusion/our-values

Security Clearance

This position requires a Department of Energy (DOE) Q-level clearance.  If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing.  Q-level clearance requires U.S. citizenship. 

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.