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Data Engineer - Clearance Required

Roles & Responsibilities

  • 8+ years of experience in data engineering or architecture, or systems engineering, preferably within a Department of War or Army environment
  • Advanced experience with data integration tools and languages (e.g., Python, SQL, or specialized MBSE tools like Cameo or MagicDraw)
  • Proven ability to perform complex data mapping and identify interdependencies in a 'system-of-systems' architecture
  • Exceptional ability to present technical data to non-technical executive audiences, focusing on resource allocation and decision-making

Requirements:

  • Data Integration Mapping: Design and implement automated workflows to facilitate cross-system data flow and visualize critical interdependencies between hardware components and software systems; monitor real-time program health
  • Redundancy Identification: Analyze large datasets of requirements across multiple programs to pinpoint duplications and drive consolidation to eliminate waste
  • Portfolio Solution Modeling: Develop and maintain data models that enable 'what-if' scenario planning and enterprise-level ontologies; assess how changes in one program impact the broader system-of-systems portfolio
  • Strategic Storytelling: Translate complex data models into narratives, dashboards, and briefings; communicate project requirements, resource gaps, and the impact of investment trade-offs to senior Army leadership

Job description

Overview:

We are seeking a Strategic Data Engineer to support a critical Army mission by transforming complex technical data into actionable insights for senior leadership. You will be responsible for building automated data flows that map hardware and software interdependencies, identifying redundant requirements to drive program efficiency, and utilizing advanced modeling techniques to conduct "what-if" drills. The ideal candidate is a master of strategic storytelling; someone who can take deep-set technical data and use it to communicate investment trade-offs and resource needs to high-level stakeholders for our Army clients.

 

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

 

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

Responsibilities:

Data Integration & Mapping: Design and implement automated workflows to facilitate cross-system data flow. Identify and visualize critical interdependencies between hardware components and software systems across the enterprise. Support the integration of data across programs and the software acquisition pathway to monitor real-time program health.

 

Redundancy Identification: Analyze large datasets of requirements across multiple programs to pinpoint duplications. Drive consolidation to eliminate waste and streamline operations.

 

Portfolio & Solution Modeling: Develop and maintain data models that allow for "what-if" scenario planning and enterprise-level ontologies to ensure consistent data definitions across various programs. Assess how changes in one program impact the broader system-of-systems portfolio.

 

Requirements Traceability: Utilize data-driven "downtracing" methods to refine solution architectures and ensure every requirement is traceable from high-level mission goals down to technical implementation.

 

Strategic Storytelling: Translate complex data models into compelling narratives, dashboards, and briefings. Clearly communicate project requirements, resource gaps, and the impact of various investment trade-offs to senior Army leadership.

Qualifications:

Required Qualifications

 

Experience: 8+ years of experience in data engineering or architecture, or systems engineering, preferably within a Department of War or Army environment.

 

Technical Proficiency: Advanced experience with data integration tools and languages (e.g., Python, SQL, or specialized MBSE tools like Cameo or MagicDraw).

 

Analytical Skills: Proven ability to perform complex data mapping and identify interdependencies in a "system-of-systems" architecture.

 

Strategic Communication: Exceptional ability to present technical data to non-technical executive audiences, focusing on resource allocation and decision-making.

 

Education: Bachelor degree in Engineering, Data Science, Computer Science, or a related technical field.

 

Desirable Qualifications

  • Certifications: Active INCOSE (ASEP/CSEP), OCSMP model certification, or something related
  • Understanding of human-centered design and UIUX best practices
  • Army Domain Knowledge: Familiarity with Army acquisition processes, CPE models, the Army's modernization priorities, and implementing data governance standards to ensure interoperability
  • Experience building data bridges or integrations between System Modeling tools (e.g., Cameo or Capella/Arcadia) and Analytics platforms (e.g., Vantage)
  • Security Clearance: Active Secret or Top Secret clearance preferred
  • Modeling Expertise: Experience with digital engineering frameworks and requirements management tools (e.g., DOORS)
  • Knowledge of Modular Open Systems Approach (MOSA) standards to ensure data portability and system interoperability

 

Location

  • Remote

Clearance

  • Ability to obtain DoW Secret

     

Target Salary Range: $101,144 - $174,591

 

Disclaimer:

The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.

 

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