Data Engineer

Overview

LMI is seeking a Data Engineer SME to support a DOD logistics data integration effort.

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.

This position requires an active Secret clearance.

Responsibilities

• Able to build and maintain Data Architecture and Data Cleaning/Transformation data pipelines.
• Skill in managing client relationships, including determining client needs/requirements, managing client expectations, and demonstrating commitment to delivering quality results.
• Ensure stable, secure, performant and highly available operations for and between system and cloud services.
• Create and update program customer specific and provide required deliverable documentation.
• Architect, implement, and sustain Data Operations (e.g. microservices, containerization, serverless architectures) and data operations tech stacks.
• Apply agile process and the industry-standard toolsets and participate in providing team dependencies, identifying risks, and providing weekly status report input.
• Apply modern data processing technologies and methods, such as databases, data lakes, etc.
• Apply modern SaaS platform, integration and extensibility concepts.
• Transform ambiguous source data, clean/transform into DOD LogIT existing solutions.
• Data Architecture validation for logistics based products in various configurations in a hybrid cloud environment supporting multiple government organizations.
• Analyze user needs and data requirements to determine feasibility of design within time and cost constraints.
• Provide advice on project costs, design concepts, or design changes given customer constraints.
• Work closely with Cybersecurity resources to document controls, support accreditation, Authority to Operate (ATO) documentation and provide metrics to comply with audits.
• Test software on various environments to identify key considerations and chalk out roadmap for future customer deployments.

Qualifications

• Minimum of a SECRET security clearance.
• Knowledge of Department of Defense (DOD) Information Technology (IT) systems.
• Experience in creating and maintaining data transformation pipelines from various sources to logistics databases.
• Knowledge of DoD processes and development efforts regarding Asset Visibility, Serialization, Item Unique Identification, and Defense Logistics Management Standards.
• Must be able to work in a highly charged and fast-paced environment to prioritize and complete assigned tasks based on guidance from senior leadership.
• Interacts across organizational teams.
• Knowledge of system life cycle management principles, including software security and usability.
• Knowledge of data engineering testing and evaluation methods.
• Working knowledge of AWS products and capabilities.
• Demonstrated experience with Amazon Web Services (AWS) managed services and capabilities in GovCloud.
• 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.
• Availability for travel to National Capital Region (NCR) and at a minimum, once a quarter. 

Target salary range: $90,324 - $155,052

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.