Data Engineer

LLNL•Livermore, CA

4d•$146,340 - $222,564•Hybrid

About The Position

Lawrence Livermore National Laboratory is hiring a Data Engineer in the Applications, Simulations, and Quality Division within the Computing Directorate, supporting Strategic Deterrence data management programs. The role builds and modernizes data systems so mission-critical scientific and engineering data can be discovered, reused, and analyzed. The engineer works with scientists, engineers, software developers, and data stewards to understand experimental and operational workflows and turn them into reliable data products. Work includes structured and unstructured data, automated pipelines, metadata and schema design, data quality and lineage, APIs, visualization, and integration with modern data platforms. The position may offer a hybrid schedule, with in-person and virtual work and the possibility of working from home one or more days per week, depending on assignment. Hiring may be at SES.2 or SES.3, depending on knowledge and related experience; the higher level has additional responsibilities and qualifications. This is a career-indefinite position open to Lab employees and external candidates.

Requirements

Ability to obtain and maintain a U.S. Department of Energy Q-level security clearance; U.S. citizenship is required.
Bachelor’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related technical field, or an equivalent combination of education and relevant experience.
Significant experience using Python or another programming language to process, transform, analyze, or validate data.
Broad experience developing data pipelines for structured or unstructured data and working with formats such as JSON, YAML, Parquet, CSV, or XML.
Comprehensive experience with data modeling, schema design, metadata, data quality, or data lineage.
Broad experience with collaborative software development practices such as Git, code review, automated testing, or documentation, and familiarity with CI/CD or containerization concepts.
Comprehensive experience integrating systems through REST APIs, databases, object storage, file-based exchange, or similar mechanisms.
Proficient, demonstrated experience working with customers or subject matter experts to define requirements and deliver technical solutions.
Proficient written and verbal communication skills to explain technical concepts, architectures, and tradeoffs to varied audiences.
At SES.3, advanced experience independently architecting and delivering complex data pipelines, platforms, or data products.
At SES.3, advanced experience analyzing complex scientific, technical, manufacturing, or business workflows and translating them into scalable data solutions.
At SES.3, significant experience providing technical direction, influencing stakeholders, and recommending systems, services, or process improvements.

Nice To Haves

Broad experience with workflow orchestration tools such as Airflow, Prefect, or Dagster.
Comprehensive experience with scientific, engineering, manufacturing, national security, or other regulated data environments.
Proficient knowledge of S3-compatible object storage, lakehouse architectures, or distributed data platforms.
Broad experience developing scientific visualizations or dashboards using Plotly, Streamlit, Tableau, or similar technologies.
Comprehensive knowledge of data architectures supporting semantic search, machine learning, knowledge graphs, or AI-enabled applications.

Responsibilities

Design, build, test, and maintain automated pipelines to ingest, transform, validate, and publish structured and unstructured scientific or engineering data.
Partner with scientists and engineers to understand workflows and translate needs into data requirements, schemas, metadata, APIs, and reusable data products.
Develop and apply data quality, lineage, governance, and metadata practices that improve data discovery, understanding, and reuse.
Build interfaces, APIs, dashboards, or other tools that help technical users explore data and use it in analysis workflows.
Apply DataOps and software engineering practices, including version control, automated testing, CI/CD, documentation, and containerization, to improve reliability and reproducibility.
Evaluate data platforms, storage technologies, and commercial or open-source tools; recommend solutions based on mission needs, security constraints, maintainability, and cost.
Communicate data architectures, tradeoffs, risks, and progress to technical and nontechnical stakeholders.
Collaborate with application, platform, data governance, and infrastructure teams to establish shared standards and integration approaches.
Perform other duties as assigned.
At SES.3, independently define and deliver solutions to complex, ambiguous data management problems spanning multiple projects, organizations, or scientific disciplines.
At SES.3, set technical direction, evaluate architectural tradeoffs, and provide technical leadership or mentorship for data engineering efforts.
At SES.3, advise management, customers, and senior technical personnel on data strategy, platform selection, and implementation approaches.