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Data Engineer (Mid-Career)

Location:  Livermore, CA
Category:  Science & Engineering
Organization:  Computing
Posting Requirement:  External w/ US Citizenship
Job ID: 107360
Job Code: Science & Engineering MTS 3 (SES.3) / Science & Engineering MTS 4 (SES.4)
Date Posted: July 31 2020
LLNL $1500 Referral Program Eligible

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Join us and make YOUR mark on the World!

Come join Lawrence Livermore National Laboratory (LLNL) where we apply science and technology to make the world a safer place; now one of 2020 Best Places to Work by Glassdoor!

Do you thrive on big data problems? Do you have a passion for creating data ingestion and transformation pipelines? As a Data Engineer, your focus will be on brining order to the chaos of managing large amounts of data. If you are looking to effect change and make an impact from the ground up, keep reading.

We are looking for a Data Engineer to help architect a data management solution for our data scientists. You will play a key role in helping to define and develop cutting edge on-prem cloud native computing environments. This position is in the Global Security Computing Applications Division (GS-CAD) within the Computing Directorate, matrixed to the Global Security Directorate.

This position will be filled at either the SES.3 or SES.4 level depending on your qualifications.  Additional job responsibilities (outlined below) will be assigned if you are selected at the higher level.

Essential Duties
- Collaborate with stakeholders, software developers, data scientist, and multidisciplinary teams to understand their data access and usage needs to develop a data infrastructure solution.
- Architect, develop and deploy data pipelines to collect, clean, and store largescale, cross-functional datasets.
- Design optimal storage, data structures, security, and retrieval mechanisms for data at rest in data lakes and analytics data store, or data in motion for real-time processing requirements.
- Design and implement pluggable framework for data ingestion and transformation workflows used on data lakes.
- Architect and develop data infrastructure platform on top of Kubernetes for our data scientist and big data researchers.
- Document and version control the data infrastructure platform, using Git and Confluence; track/report work status in tickets using JIRA.
-Perform other duties as assigned.

In Addition at the SES.4 Level
- Develop technical strategy for our data infrastructure platform and be accountable for the execution of its roadmap.
- Provide input, recommendations and presentations on technical issues to management.

Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, or related field, or the equivalent combination of education and related experience.
- Significant experience working in data science teams to provide robust data engineering solutions or a background in Data science, Data mining, Multivariate statistics, Computer vision, Machine learning.
- Significant experience working with diverse, multi modal, and very large datasets.
- Deep technical knowledge of big data infrastructure practices such as data wearhousing, and/or data lakes.
- Significant experience with databases (e.g. SQL, NoSQL, MySQL, Mongo) and high-performance or distributed processing (e.g. using MapReduce, Spark, Pig, Presto, and/or Hive).
- Experience in one or more of the advanced areas: container technology, data analysis, data management, software engineering, and big data technologies.
- Excellent interpersonal skills necessary to interact with all levels of personnel and ability to work independently in a multi-disciplinary team environment.

In Addition at the SES.4 Level
- Substantial experience as a technical lead on advanced projects, achieving positive results, and driving projects to closure on time.
- Substantial experience providing technical leadership and mentoring other engineers for best practices on data engineering.
- Expert verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information and provide advice to management.

Desired Qualifications
- Master’s degree in Computer Science, Computer Engineering, or a related field.
- Experience developing data infrastructure platform(s), and/or big data applications.

Pre-Employment Drug Test:  External applicant(s) selected for this position will be required to 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.

Security Clearance:  This position requires a Department of Energy (DOE) Q-level clearance.

If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing.  Q-level clearance requires U.S. citizenship.  If you hold multiple citizenships (U.S. and another country), you may be required to renounce your non-U.S. citizenship before a DOE L or Q clearance will be processed/granted.  For additional information, please see DOE Order 472.2

Note:   This is a Career Indefinite position. Lab employees and external candidates may be considered for this position.

About Us

Lawrence Livermore National Laboratory (LLNL), located in the San Francisco Bay Area (East Bay), is a premier applied science laboratory that is part of the National Nuclear Security Administration (NNSA) within the Department of Energy (DOE).  LLNL's mission is strengthening national security by developing and applying cutting-edge science, technology, and engineering that respond with vision, quality, integrity, and technical excellence to scientific issues of national importance.  The Laboratory has a current annual budget of about $2.3 billion, employing approximately 6,900 employees.

 

LLNL is an affirmative action/ equal opportunity employer. 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, protected veteran status, age, citizenship, or any other characteristic protected by law.