Data Engineer

Lawrence Livermore National Laboratory
Livermore, CA, United States
17 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$146,340.0 - $185,544.0
Working hours
Shift work

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Airflow Amazon S3 Automation of Tests Code Review Databases Continuous Integration Data Architecture Information Engineering Data Governance Data Infrastructure
+31 more
Data Systems Distributed Data Store Graph Database JSON Python (Programming Language) Machine Learning Metadata Open Source Technology DataOps Search Technologies Software Engineering Systems Integration Tableau (Software) Unstructured Data Extensible Markup Language (XML) YAML Parquet Delivery Pipeline Data Strategy Git Containerization Storage Technologies Information Technology Data Lineage Plotly Data Management Restful APIs Streamlit Framework Software Version Control Data Pipelines Programming Languages

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.

Requirements

  • 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.

Qualifications we desire

  • 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.

Benefits & conditions

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

$175,530 - $222,564 Annually for the SES.3 level, * Included in 2026Best Places to Work by Glassdoor!

  • FlexibleBenefits Package
  • 401(k)
  • Relocation Assistance
  • Education Reimbursement Program
  • Flexible schedules (*depending on project needs)
  • Our values - visithttps://www.llnl.gov/inclusion/our-values

About the company

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.

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