Leidos is seeking an accomplished mid-level Data Engineer to support and implement a large data architecture and management strategy on a large, complex and distributed simulation training system. This position will work under a data architect, interact with software engineers and system engineers, and encompass the necessary strategy, plans, implementation, validation and operation of a large scale data operation. The position will involve a large degree of autonomy and requires a candidate with a high level of independent initiative.
A successful candidate will take the lead on the hands-on development and implementation of data solutions across the entire program. Operational aspects involving cloud deployment, network limited/denied environments, latency issues, data redundancy and backups touch on a few of the more significant issues to be resolved. Candidate must demonstrate an understanding of the various approaches and tools available to trade off design considerations to arrive at optimal solutions. A knowledge of AI/ML is considered essential to success. Detailed experience with structured and unstructured data should be evident in the candidates experience. The solution will involve diverse sources including “big data” and engaged in issues related to data quality in large data lakes. As part of the larger team, the candidate will represent the data aspects of the system in collaborative IPTs and scrums in an Agile environment.
A successful candidate will be well versed in the implementation of data management strategies, data technologies, and the current state of the art in managing data streams involving as ,much as peta-bytes of data annually. Candidate must be able to define and explain the processes to validate the solutions and be able to demonstrate success to the user community as well as other program stakeholders. Candidate will hold the role of an internal team expert in data management and must be able to participate in data modeling and data discussions in the larger context of the overall program. Candidate must work well with a senior data architect to flesh out the plans and solutions developed. A successful candidate should also demonstrate the ability to work with a more junior staff managing the day to day activity and tracking both risks and progress.
Possess or be able to acquire a DOD Secret clearance
BS in appropriate technical field
Possess at least 4 years of hands-on experience in data architecture, implementation and big data analysis
Demonstrate success in data lakes and AI/ML implementation
Demonstrate success in big data in a distributed and potentially unstable or network denied environment
Specific experience within the DOD network
Demonstrated understanding of DOD security issues
Published papers related to data management and data distribution issues related to data latency
External Referral Bonus:Ineligible
Potential for Telework:Yes, 100%
Clearance Level Required:None
Travel:Yes, 10% of the time
Scheduled Weekly Hours:40
Job Family:Data Scientist
Leidos is a Fortune 500® information technology, engineering, and science solutions and services leader working to solve the world’s toughest challenges in the defense, intelligence, homeland security, civil, and health markets. The company’s 40,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Virginia, Leidos reported annual revenues of approximately $12.30 billion for the fiscal year ended January 1, 2021. For more information, visit www.Leidos.com.
Pay and Benefits
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Commitment to Diversity
All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.