Data Engineer

Lawrence Livermore National Laboratory

Livermore (CA)

Hybrid

USD 146,000 - 223,000

Full time

20 hours ago
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Job summary

Lawrence Livermore National Laboratory seeks a Data Engineer to build and modernize data systems for discoverable, reusable data. You will partner with scientists, engineers, and data stewards to translate workflows into reliable data products and pipelines across structured and unstructured data.

The role spans metadata, quality, APIs, dashboards, and data platform integration within the Computing Directorate. Hybrid work flexibility may apply; U.S.

Qualifications

  • U.S. citizenship and ability to obtain DOE Q clearance.
  • Bachelor’s degree in CS, Engineering, Math, Data Science, or related field.
  • Significant experience with Python and data processing.
  • Experience building data pipelines for structured or unstructured data.
  • Experience with data modeling, metadata, data quality, or data lineage.
  • Proficient in Git, automated testing, and CI/CD.
  • Experience integrating systems via REST APIs and storage.

Responsibilities

  • Design, build, test, and maintain automated pipelines that ingest, transform, validate, and publish data.
  • Collaborate with scientists and engineers to translate workflows into data requirements and products.
  • Develop data quality, lineage, governance, and metadata practices.
  • Build interfaces, dashboards, or tools to explore data for analysis workflows.
  • Apply DataOps and containerization to improve reliability and reproducibility.
  • Evaluate data platforms and tools, and recommend solutions based on needs and constraints.
  • Communicate architectures, risks, and progress to stakeholders.
  • Collaborate across teams to establish shared standards and integration approaches.
  • Perform other duties as assigned.

Skills

Python
Data pipelines
Data modeling
REST APIs
Git
CI/CD
Data governance

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or related field

Tools

Airflow
Dagster
Prefect
Tableau
Plotly

Job description

Mid-Senior Level | Full-time
Information Technology/Computing | Livermore, CA | 10/21/2026
Reference #: REF8951D
Job Code: SES.2 Science & Engineering MTS 2 / SES.3 Science & Engineering MTS 3
Organization: Computing
Position Type: Career Indefinite
Security Clearance: Anticipated DOE Q clearance (requires U.S. citizenship and a federal background investigation)
Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
Medical Exam: Not applicable

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

Job Description

We have an opening for a Data Engineer to build and modernize data systems that make mission-critical scientific and engineering data discoverable, reusable, and available for analysis. You will partner with scientists, engineers, software developers, and data stewards to understand complex experimental and operational workflows and translate them into reliable data products.

The work spans structured and unstructured data, automated pipelines, metadata and schema design, data quality and lineage, APIs, visualization, and integration with modern data platforms. You will have opportunities to improve legacy processes, introduce reusable engineering practices, and help shape how research data is managed and shared within LLNL and across the National Nuclear Security Administration complex.

This position is in the Applications, Simulations, and Quality Division within the Computing Directorate, supporting Strategic Deterrence data management programs.

Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.

This position will be filled at either level based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities and qualifications will apply if hired at the higher level.

You will

  • Design, build, test, and maintain automated pipelines that ingest, transform, validate, and publish structured and unstructured scientific or engineering data.
  • Partner with scientists and engineers to understand their workflows and translate their needs into data requirements, schemas, metadata, APIs, and reusable data products.
  • Develop and apply data quality, lineage, governance, and metadata practices that make data easier to discover, understand, and reuse.
  • Build interfaces, APIs, dashboards, or other tools that allow technical users to explore data and incorporate it into 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, and recommend solutions based on mission needs, security constraints, maintainability, and cost.
  • Communicate data architectures, tradeoffs, risks, and progress clearly to technical and nontechnical stakeholders.
  • Collaborate across application, platform, data governance, and infrastructure teams to establish shared standards and integration approaches.
  • Perform other duties as assigned.

Additional job responsibilities at the SES.3 level

  • Independently define and deliver solutions to complex, ambiguous data management problems spanning multiple projects, organizations, or scientific disciplines.
  • Set technical direction, evaluate architectural tradeoffs, and provide technical leadership or mentorship for data engineering efforts.
  • Advise management, customers, and senior technical personnel on data strategy, platform selection, and implementation approaches.
Qualifications
  • Ability to obtain and maintain a U.S. Department of Energy Q-level security clearance, which requires U.S. citizenship.
  • 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 using collaborative software development practices such as Git, code review, automated testing, or documentation, with familiarity with CI/CD or containerization concepts.
  • Comprehensive experience integrating systems through REST APIs, databases, object storage, file-based exchange, or similar mechanisms.
  • Proficient and demonstrated experience working with customers or subject matter experts to define requirements and deliver technical solutions.
  • Proficient written and verbal communication skills necessary to explain technical concepts, architectures, and tradeoffs to a range of audiences.

Additional qualifications at the SES.3 level

  • Advanced experience independently architecting and delivering complex data pipelines, platforms, or data products.
  • Advanced experience analyzing complex scientific, technical, manufacturing, or business workflows and translating them into scalable data solutions.
  • Significant experience providing technical direction, influencing stakeholders, and recommending systems, services, or process improvements.
  • 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 tools such as Plotly, Streamlit, Tableau, or similar technologies.
  • Comprehensive knowledge of data architectures supporting semantic search, machine learning, knowledge graphs, or AI-enabled applications.
Pay Range

Pay Range

$146,340 - $185,544 Annually for the SES.2 level

$175,530 - $222,564 Annually for the SES.3 level

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Position Information

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

Why Lawrence Livermore National Laboratory?
  • Included in 2026Best Places to Work by Glassdoor!
  • Flexible schedules (*depending on project needs)

This position requires a Department of Energy (DOE) Q-level clearance.If you are selected, wewill initiate a Federal background investigation to determine if youmeet 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 useand/or possession ofmobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area whereyou are not permitted to have a personal and/or laboratory mobile devicein your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.

Ifyou useamedical device, whichpairs with a mobile device,you must still follow the rules concerningthe mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities requireseparate 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.

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.

CaliforniaPrivacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitlesjob 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 .

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