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Python Data Engineer Jobs

Lawrence Livermore National Laboratory

Aalyria

SESLOC Credit Union

Hybrid

Onsite

Information Technology

At SESLOC, it is the people that make the place. Rooted in academics, and locally headquartered for over 80 years, we are the credit union with the funny name. But to us, financial dreams and goals are serious business. 
 
Job Summary:
The Data Engineer is responsible for the effective management and governance of SESLOC's data assets, supporting data scale, quality and compliance across the organization. This role includes developing and maintaining data governance practices, supporting compliance with data policies and regulations, and partnering with SESLOC's data analytics community. This position works with the technology that collects, stores and processes SESLOC's data assets and plays a key role in maintaining data quality, integrity, security, reliability and accessibility through the application of strong data management practices.
 
For a detailed description of job responsibilities, please view the attached job description. 
 
Key Qualifications:
<ul>
<li style="color:#000000;">Experience applying data governance frameworks (DAMA-DMBok, DCAM and COBIT) preferred</li>
<li style="color:#000000;">Familiarity with data warehousing concepts and structures</li>
<li style="color:#000000;">Experience with business intelligence (BI) tools or data visualization tools (e.g. Spotfire, Tableau, Power BI)</li>
<li style="color:#000000;">Experience with data quality, data modeling and data integrity tools and practices</li>
<li style="color:#000000;">Ability to analyze datasets, identify trends and anomalies, and recommend data quality improvements</li>
<li style="color:#000000;">Ability to work collaboratively with cross-functional teams to promote data literacy and data best practices</li>
<li style="color:#000000;">Experience solving ETL related challenges, including troubleshooting and optimization </li>
<li style="color:#000000;">Proficiency in SQL for querying and managing databases and Python or R for data manipulation and analysis </li>
<li style="background:#FFFFFF;">Ability to remain informed about industry trends and developments that affect the role, business area(s) and the Information Technology environment.</li>
</ul>
Education/Experience:
<ul>
<li>A bachelor's degree with an emphasis in Computer Science, Information Technology, Data Science and two to four years of progressive experience in data management, data analytics, data governance or related field. </li>
</ul>
 
SESLOC has a collegial, team focused work environment. We offer competitive compensation and excellent benefits including fully paid employee medical, dental and vision; vacation, sick, holiday time off; and a 401k with generous employer match.
Be sure to attach a cover letter explaining how you are the perfect fit for this role and a current resume.
 
EOE As part of the recruitment process, SESLOC may run a bond check, credit check and criminal history check as part of the recruitment process.&nbsp; If SESLOC runs these reports, we will obtain your authorization first.&nbsp;

Data Engineer

Data governance, ETL, SQL, Python/R; data warehousing and BI tools; bachelor's in CS/IT/Data Science; 3–5 years in data engineering or related fields.

Company Description: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.&#xa0;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&#xa0;have multiple openings for a&#xa0;Data Science Engineer with a background in applied machine learning and data science for cybersecurity and power systems applications. You will design, build, and deploy novel data science capabilities to enhance the reliability and adversarial resilience of critical infrastructure. You will write code, create analytical tools and visualizations, diagnose complex systems, and discover innovative approaches to challenging problems. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate, in support of Global Security’s Energy and Homeland Security (E) program.Depending on your assignment, these positions 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.These positions will be filled at either&#xa0;level based on knowledge and related experience as assessed by the responsibilities (outlined below) will be assigned if hired at the higher level.You will<ul><li>Design, develop, and apply machine learning and data science algorithms, including deep learning and modern AI techniques such as neural networks, transformers, and generative models, to analyze cybersecurity and power systems data.</li><li>Analyze data and build analytical capabilities to improve the reliability and adversarial resilience of critical infrastructure.</li><li>Write code to implement and deploy data science solutions and analytical tools, create visualizations, and follow software engineering best practices for code quality, testing, and documentation.</li><li>Collaborate with multidisciplinary teams including cybersecurity experts, power systems engineers, and computer scientists.</li><li>Support building research prototypes and capabilities for critical infrastructure protection, contributing to the development of new methodologies and tools.</li><li>Provide solutions to moderately complex to complex data analytics challenges in the cybersecurity and power systems domains, using established and innovative methods.</li><li>Perform other duties as assigned.</li></ul>Additional job responsibilities, at the SES.3 level<ul><li>Lead highly complex projects with technical and analytic challenges, developing innovative solutions and building advanced capabilities.</li><li>Discover and pioneer new approaches to data science problems, pushing the boundaries of current methodologies, and transforming ideas from concepts to operational solutions.</li><li>Present technical work and results to sponsors and technical audiences on a regular basis, demonstrating capabilities through hands-on demonstrations and deep technical discussions.</li><li>Contribute to technical direction and strategy for data science capabilities in critical infrastructure protection by building proof-of-concept systems, demonstrating new approaches, and contributing ideas to research proposals.</li></ul>Qualifications:<ul><li>Ability to secure&#xa0;and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.</li><li>Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field, or the equivalent combination of education and related experience.</li><li>Broad experience with Python programming and software development.</li><li>Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems.</li><li>Intermediate&#xa0;knowledge of software engineering best practices including version control, unit testing, and documentation.</li><li>Proficient verbal and written communication skills necessary to collaborate within a team environment and present technical information to varied audiences.</li><li>Effective interpersonal skills and initiative necessary to interact with all levels of personnel and work independently in a collaborative, multidisciplinary team environment.</li><li>Demonstrated ability to balance multiple projects and prioritize competing demands while maintaining high-quality standards for deliverables.</li></ul>Additional qualifications at the SES.3 level&#xa0;<ul><li>Advanced experience in applied machine learning and data science with demonstrated ability to deliver complex technical solutions independently.</li><li>Advanced experience building innovative data science systems and discovering novel approaches to complex problems.</li><li>Experience presenting technical work and demonstrations to both technical and non-technical audiences, including sponsors and stakeholders.</li></ul>Qualifications We Desire<ul><li>Master’s degree or PhD&#xa0;in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical field.</li><li>Experience with modern machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, and/or similar tools.</li><li>Experience with deep learning techniques, transformer models, retrieval-augmented generation (RAG), fine-tuning pre-trained models, or adapting foundation models for specific application domains.</li><li>Knowledge of cybersecurity principles and practices, including threat detection, anomaly detection, or security analytics.</li><li>Experience with power systems, SCADA systems, industrial control systems, or operational technology environments.</li><li>Experience with data visualization and effectively communicating analytical results to diverse audiences.</li></ul>&#xa0;Pay Range$146,340 - $222,564 Annually$146,340 - $185,544 Annually for the SES.2 level$175,530 - $222,564 Annually for the SES.3 levelThis 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.&#xa0;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:#LI-Hybrid<div sr-tagline=""></div>Position InformationThis is a Career Indefinite position, open to Lab employees and external candidates.
Why Lawrence Livermore National Laboratory?<ul><li>Included in 2026&#xa0;Best Places to Work by Glassdoor!</li><li>Flexible&#xa0;<a href="https://www.llnl.gov/join-our-team/culture/benefits" rel="noopener noreferrer">Benefits Package</a></li><li>401(k)</li><li>Relocation Assistance</li><li>Education Reimbursement Program</li><li>Flexible schedules (*depending on project needs)</li><li>Our values - visit&#xa0;<a href="https://www.llnl.gov/diversity/our-values" rel="noopener noreferrer">https://www.llnl.gov/inclusion/our-values</a></li></ul>
Security ClearanceThis position requires a Department of Energy (DOE) Q-level clearance.&#xa0;&#xa0;If you are selected, we&#xa0;will initiate a Federal background investigation to determine if you&#xa0;meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing.&#xa0; Q-level clearance requires U.S. citizenship.&#xa0;
Pre-Employment Drug TestExternal 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 DevicesPer the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use&#xa0;and/or possession of&#xa0;mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where&#xa0;you are not permitted to have a personal and/or laboratory mobile device&#xa0;in your possession.&#xa0; This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.&#xa0;&#xa0;If&#xa0;you use&#xa0;a&#xa0;medical device, which&#xa0;pairs with a mobile device,&#xa0;you must still follow the rules concerning&#xa0;the mobile device in individual sections within Limited Areas.&#xa0; Sensitive Compartmented Information Facilities require&#xa0;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 advertisementsPlease 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:&#xa0;<a href="https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf" rel="noopener noreferrer">https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf</a>
Equal Employment OpportunityWe 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 AccommodationOur goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.&#xa0; If you need a reasonable accommodation during the application or the recruiting process, please use our <a href="https://www.llnl.gov/join-our-team/careers/accessibility" rel="noopener noreferrer">online form</a> to submit a request.&#xa0;
California&#xa0;Privacy NoticeThe California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles&#xa0;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 <a href="https://www.llnl.gov/join-our-team/careers/privacy-statement" rel="noopener noreferrer">here</a>.

Data Science Engineer

Bachelor’s degree in CS/Data Science/Engineering/Math/Statistics or related field; strong Python; ML experience; software engineering basics; ability to obtain DOE Q clearance; good communication.

Company Description: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.&#xa0;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 an Energy Resilience Data Scientist. This role sits at the intersection of data science, energy systems, and critical infrastructure resilience, helping transform complex, multi-source data into actionable insights for resilience planning and risk assessment. In this role, you will develop data-driven and applied machine learning methods to assess, model, and improve the resilience of energy systems. You will combine applied research and critical thinking to understand complex, heterogeneous datasets, build predictive and decision-support models, and communicate results to multidisciplinary engineering teams and program sponsors. You will support LLNL’s Cyber and Infrastructure Resilience (CIR) program’s growing research portfolio in electric grid infrastructure. This position is in the Computational Engineering Division (CED),&#xa0;within the Engineering Directorate.This position will be filled at either&#xa0;level based on knowledge and related experience as assessed by the responsibilities (outlined below) will be assigned if hired at the higher level.You will<ul><li>Develop and apply data science and machine learning methods to characterize and assess energy infrastructure resilience under a range of disruptions, including natural hazards, extreme weather, infrastructure failures, and other stressors.</li><li>Build, train, and evaluate data-driven models, selecting appropriate architectures and metrics for the mission problem.</li><li>Integrate heterogeneous data sources into reproducible analytics pipelines.</li><li>Collaborate with multidisciplinary engineering teams to iterate on model design, evaluation, and application, and deliver validated results.</li><li>Produce clear technical documentation, reports, and briefings.</li><li>Publish research results in peer-reviewed journals, conference proceedings, and laboratory reports, as appropriate.</li><li>Routinely interact with technical contacts at sponsor and partner organizations.</li><li>Support the growth of the laboratory’s energy resilience research portfolio through collaboration across programs and disciplines.</li><li>Perform other duties as assigned.</li></ul>Additional job responsibilities, at the SES.3 level&#xa0;<ul><li>Provide technical leadership and guidance to multiple diverse, technical teams of LLNL scientists and engineers to operationalize research and development advancements for LLNL national security programs, while executing projects and tasks and balancing priorities of customers and partners to ensure deadlines are met.</li><li>Independently determine technical objectives and criteria to satisfy project deliverables and execute the appropriate technical approaches.</li><li>Serve as the technical point of contact for program managers at sponsor and partner organizations by sharing relevant advanced level knowledge, providing opinions and recommendations on methodologies, and exerting influence as needed to fulfill deliverables and best meet sponsor needs.</li></ul>Qualifications:<ul><li>Ability to secure&#xa0;and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.</li><li>Master’s degree in data science, applied statistics, computer science, engineering or a related field, or equivalent combination of education and relevant experience.</li><li>Comprehensive knowledge and experience with one or more of the following computational disciplines: applied machine learning, statistical modeling, risk analysis, data analytics.</li><li>Comprehensive experience in applied machine learning, including developing and evaluating models using PyTorch or TensorFlow.</li><li>Strong Python programming skills, including experience with the scientific Python stack for data science (NumPy, SciPy, Matplotlib).&#xa0;Demonstrated experience performing geospatial analytics in Python, using GeoPandas or equivalent geospatial tools and libraries.</li><li>Comprehensive knowledge and experience in developing data-driven models and/or frameworks to characterize and assess infrastructure systems and/or threats and risks to these systems.</li><li>Proficient verbal and written communication skills necessary to effectively collaborate in a multi-disciplinary team delivering results on schedule and adapting to evolving requirements.</li><li>Demonstrated analytical, problem-solving, and decision-making skills to effectively develop creative solutions to moderately complex problems.</li><li>Ability to travel off-site for sponsor and customer interactions.</li></ul>Additional qualifications at the SES.3 level&#xa0;<ul><li>PhD&#xa0;in data science, applied statistics, computer science, engineering or a related field, or the equivalent combination of education and related experience.</li><li>Advanced level knowledge in one or more of the following areas: infrastructure systems, energy systems, or other related discipline. Advanced knowledge and experience with one or more of the following computational disciplines: applied machine learning, statistical modeling, risk analysis, data analytics.</li><li>Significant experience and advanced knowledge in developing data-driven models and/or frameworks to characterize and assess energy systems and/or threats and risks to these systems.</li><li>Significant leadership skills and experience and demonstrated ability to exercise independent judgment to effectively manage diverse technical teams in executing projects. Ability to independently develop and execute complex analyses and to prepare and finalize tailored reports.</li></ul>Qualifications We Desire<ul><li>Experience with energy systems, grid operations, infrastructure resilience, risk analysis, hazard impacts, or interdependency modeling.</li><li>Experience with analyzing disruptions resulting from complex threat scenarios.</li><li>Comprehensive knowledge and broad experience building models and running simulations using Python.</li><li>Broad experience in managing multiple concurrent projects.</li></ul>&#xa0;Pay Range$146,340 - $222,564 Annually$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.&#xa0;Additional Information:#LI-Hybrid<div sr-tagline=""></div>Position InformationThis is a Career Indefinite position, open to Lab employees and external candidates.
Why Lawrence Livermore National Laboratory?<ul><li>Included in 2026&#xa0;Best Places to Work by Glassdoor!</li><li>Flexible&#xa0;<a href="https://www.llnl.gov/join-our-team/culture/benefits">Benefits Package</a></li><li>401(k)</li><li>Relocation Assistance</li><li>Education Reimbursement Program</li><li>Flexible schedules (*depending on project needs)</li><li>Our values - visit&#xa0;<a href="https://www.llnl.gov/diversity/our-values">https://www.llnl.gov/inclusion/our-values</a></li></ul>
Security ClearanceThis position requires a Department of Energy (DOE) Q-level clearance.&#xa0;&#xa0;If you are selected, we&#xa0;will initiate a Federal background investigation to determine if you&#xa0;meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing.&#xa0; Q-level clearance requires U.S. citizenship.&#xa0;
Pre-Employment Drug TestExternal 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 DevicesPer the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use&#xa0;and/or possession of&#xa0;mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where&#xa0;you are not permitted to have a personal and/or laboratory mobile device&#xa0;in your possession.&#xa0; This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.&#xa0;&#xa0;If&#xa0;you use&#xa0;a&#xa0;medical device, which&#xa0;pairs with a mobile device,&#xa0;you must still follow the rules concerning&#xa0;the mobile device in individual sections within Limited Areas.&#xa0; Sensitive Compartmented Information Facilities require&#xa0;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 advertisementsPlease 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:&#xa0;<a href="https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf">https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf</a>
Equal Employment OpportunityWe 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 AccommodationOur goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.&#xa0; If you need a reasonable accommodation during the application or the recruiting process, please use our <a href="https://www.llnl.gov/join-our-team/careers/accessibility">online form</a> to submit a request.&#xa0;
California&#xa0;Privacy NoticeThe California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles&#xa0;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 <a href="https://www.llnl.gov/join-our-team/careers/privacy-statement">here</a>.

Energy Resilience Data Scientist

DOE Q clearance; Master’s in data science, CS, engineering, or related field; strong ML (PyTorch/TF); Python; geospatial analytics; able to travel; capable of communicating across teams.

Software Developer in Test (FSO) - Tightbeam

Software Developer in Test

BS in CS or EE; 3+ years in software dev with test automation; Python/C++; HW-in-the-loop/test tooling; data analysis; cross-functional collaboration.

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