Data Management Engineer

LLNL•Livermore, CA

2d•Hybrid

About The Position

We have an opening for an experienced Data Management Engineer to enable seamless data access and delivery across our enterprise business systems, such as Finance, HR, and Procurement. This role will focus on curating data to enable 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. This position is in the Enterprise Application Services (EAS) Division within the Computing Directorate, in support of the LivIT Program. 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.

Requirements

Ability to obtain and maintain a U.S. DOE L-level security clearance in the future; this requires U.S. citizenship.
Bachelor’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 applying data virtualization concepts in a production or enterprise environment, preferably through use of Denodo.
Advanced knowledge of business operations data, for example ERP systems such as Oracle Finance, Oracle HCM Cloud, PeopleSoft, or Hexagon/Infor EAM.
Significant experience with SQL, data modeling, metadata management, and data cataloging.
Advanced verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information and provide advice to management.

Nice To Haves

Denodo Platform Certified Architect or Developer.
Significant experience working within Agile/Scrum environments supporting cross-functional development teams.
Exposure to AI and ML tooling ecosystems, for example Databricks, Azure ML, or SageMaker.
Advanced experience with cloud data platforms, for example Snowflake, Redshift, BigQuery, or Databricks, and API-based data access.
Familiarity with data privacy laws, data residency, and compliance relevant to Finance, HR, and health-related data.

Responsibilities

Conduct technical tasks in design, implementation, and management with data virtualization layers using tools such as Denodo to provide a unified view of enterprise data across on-prem and cloud systems.
Collaborate with enterprise development teams on complex problems, virtualizing data sources relevant to Finance, HR, Procurement, Supply Chain, and other operational domains.
Curate data and semantic layers to streamline AI and ML workflows.
Partner with development teams to leverage existing enterprise data and create new data structures in a Denodo data virtualization environment.
Collaborate 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.