LMI is seeking a Data Engineer to support a DOD Navy Program.

LMI is a consultancy dedicated to powering a future-ready, high-performing government, drawing from expertise in digital and analytic solutions, logistics, and management advisory services. We deliver integrated capabilities that incorporate emerging technologies and are tailored to customers' unique mission needs, backed by objective research and data analysis. Founded in 1961 to help the Department of Defense resolve complex logistics management challenges, LMI continues to enable growth and transformation, enhance operational readiness and resiliency, and ensure mission success for federal civilian and defense agencies.

LMI has been named a 2022 and 2024 #TopWorkplace in the United States by Top Workplaces! We are honored to be recognized as a company that values a people-centered culture, and we are grateful to our employees for making this possible!

This position requires an active Secret clearance.  

The Data Engineer will provide support to the customer by building, managing, and operationalizing data pipelines. You will work as part of a team with other contractors, government civilians, and military personnel in an agile environment.

The Data Engineer duties may include:

• Implementing data management standards, data requirements, and data specifications.
• Develop, implement, and maintain data storage capabilities.
• Develop secure code and error handling.
• Program custom data algorithms.
• Apply data acquisition, cleaning, transformation, and ingestion best practices for machine learning data conduits.
• Assess and address the limitations of methods to deliver data.
• Assist integrated project teams to identify, curate, and manage data.
• Build automated data management conduits.
• Comply with data classification and handling requirements through access control and security best practices.
• Manipulate and clean large, disparate datasets for bulk analysis to identify connections.
• Read, interpret, write, modify, and execute simple scripts (e.g., PERL, VBS) on Windows and UNIX systems (e.g., those that perform tasks such as: parsing large data files, automating manual tasks, and fetching/processing remote data).
• Manage the compilation, cataloging, caching, distribution, and retrieval of data.
• Perform secure programming and identify potential flaws in codes to mitigate vulnerabilities.
• Record and manage test and operational datasets.
• Skill in establishing data security controls.
• Skill in developing data dictionaries.
• Skill in writing scripts using R, Python, PIG, HIVE, SQL, etc.
• Ability to collect, verify, and validate test data.
• Knowledge of container orchestration and resource management platforms.
• Interact professionally with clients/internal teams; gather requirements and document the work in a ticketing system, designing and implementing new feature additions and improvements. 
• Utilize industry standard tools such as Gitlab for code version control, project management, product requirements, and user documentation.
• Work directly with the customer to gather requirements and product feedback for future iterations.
• Support capabilities briefings for military personnel.
• Strong ability to analyze business requirements and create solutions.
• Ability to troubleshoot problems and provide timely resolutions.
• Clearly communicate with product owners to understand business concerns and demonstrate proposed solutions for acceptance.
• High energy, enthusiasm, tact, ability to effectively interact with senior executives from Government and industry.
• Ability to create and foster a cooperative work environment.
• Self-directed, detail oriented in completing assigned tasks, able to adapt to changing work efforts and manage impact of shifting priorities.
• Work closely with Cybersecurity resources to document controls, support accreditation, Interim Authorization to Test (IATT) and Authority to Operate (ATO) documentation and provide metrics to comply with audits.
• Availability for occasional travel.

Core KSATs for DoD Cyber Workforce (DCWF):

• Knowledge of computer networking concepts and protocols, and network security methodologies.
• Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).
• Knowledge of national and international laws, regulations, policies, and ethics as they relate to cybersecurity.
• Knowledge of cybersecurity principles.
• Knowledge of cyber threats and vulnerabilities.
• Knowledge of specific operational impacts of cybersecurity lapses.
• Knowledge of cloud computing service models Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).
• Knowledge of cloud computing deployment models in private, public, and hybrid environment and the difference between on-premises and off-premises environments.

Minimum:

• DOD Cyber Workforce (DCWF) 8140 (451) System Administrator role: A BS degree in Information Technology, Cybersecurity, Data Science, Information Systems, or Computer Science, from an ABET accredited or CAE designated institution fulfills the educational requirement for this WRC (conferred within 5 years or able to prove continuous relevant work experience) -OR- Personnel Certifications: Cloud+ or GICSP or SSCP or Security+ or GSEC. If none, must be willing to obtain in first 30-days.
• 5+ years of data engineering experience.
• Proficiency in Python.
• Proficiency in query languages such as SQL.
• Proficiency in leveraging APIs.
• Experience in DOD AWS environments.
• Proficiency in moving data in AWS environments, hybrid, and on-prem systems.
• Demonstrated ability to use MS Office Suite to include Word, PowerPoint, and Excel.
• Familiarity with Cross Domain Solutions.
• Knowledge of data mining and data storage principles.
• Knowledge of database management systems, query languages, table relationships, and views.
• Knowledge of data operations processes and best practices.
• Knowledge of how to collect, store, and monitor data.
• Superior communication skills, both oral and written.
• Active Secret clearance required.

Preferred:

• Implement data mining and data warehousing applications.
• Maintain current knowledge of advancements in DoD AI Ethical Principles and Responsible AI.
• Knowledge of DoD AI Ethical Principles (e.g., responsible, equitable, traceable, reliable, and governable).
• Knowledge of how AI solutions integrate with cloud or other IT infrastructure.
• Knowledge of how to automate development, testing, security, and deployment of AI/machine learning-enabled software to the DoD.
• Knowledge of laws, regulations, and policies related to AI, data security/privacy, and use of publicly procured data for government.