Data Engineer (Supply Chain) - Clearance Required

LMI Government Consulting; United States; Remote; USD 108,000 - 161,000; Full time

Job summary

LMI is seeking a Supply Chain Data Analyst / Engineer to integrate, analyze, and transform complex parts, supplier, procurement, inventory, and risk data to support defense logistics decisions. The role builds repeatable workflows that connect parts to sources, resolves inconsistent identifiers, and makes findings traceable to sources.

Collaboration with supply chain analysts and technical experts is essential.

Qualifications

• Experience integrating, transforming, and analyzing data from multiple sources.
• Proficiency in SQL and Python or comparable data processing tools.
• Experience designing structured datasets, data pipelines, and quality assurance checks.
• Ability to resolve inconsistent identifiers and document matching methods and exceptions.
• Experience producing analytical outputs that can be reviewed and used by nontechnical stakeholders.
• Strong collaboration and communication skills, including the ability to work with subject matter experts.
• Ability to document assumptions, data provenance, and analytical limitations.

Responsibilities

• Ingest, clean, transform, and integrate parts, assembly, supplier, procurement, inventory, and risk datasets.
• Develop methods to match part numbers, NSNs/NIINs, CAGE codes, drawing identifiers, and other inconsistent records.
• Build and maintain a structured assessment dataset that connects parts to higher assemblies, sources, evidence, risks, and actions.
• Automate repeatable screening and data quality checks while routing ambiguous matches for analyst review.
• Document data lineage, refresh dates, matching logic, and confidence measures.
• Develop analytical queries and views that surface long lead times, supplier concentration, stock-outs, delivery delays, and other potential constraints.
• Partner with domain experts to develop and validate lead-time, capacity, or schedule estimates where appropriate.
• Support rolling updates as new parts lists, procurement records, and supplier information become available.
• Translate user needs into practical data products and explain the limitations of the underlying data.

Skills

SQL

Python

Data pipelines

Data quality checks

Job description

Overview

LMI is seeking a Supply Chain Data Analyst / Engineer to integrate and analyze complex parts, supplier, procurement, inventory, and risk data in support of industrial base decisions. This individual will build repeatable workflows that connect an indentured parts list to relevant government and commercial data, resolve inconsistent identifiers, and make analytical findings traceable to their sources. Working closely with supply chain analysts and technical experts, the Data Analyst / Engineer will help the team identify potential constraints at scale and focus manual investigation where it will have the greatest value. The ideal candidate combines strong data engineering and analytical skills with an interest in defense logistics and supply chain challenges.

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

• Ingest, clean, transform, and integrate parts, assembly, supplier, procurement, inventory, and risk datasets.
• Develop methods to match part numbers, NSNs/NIINs, CAGE codes, drawing identifiers, and other inconsistent records.
• Build and maintain a structured assessment dataset that connects parts to higher assemblies, sources, evidence, risks, and actions.
• Automate repeatable screening and data quality checks while routing ambiguous matches for analyst review.
• Document data lineage, refresh dates, matching logic, and confidence measures.
• Develop analytical queries and views that surface long lead times, supplier concentration, stock-outs, delivery delays, and other potential constraints.
• Partner with domain experts to develop and validate lead-time, capacity, or schedule estimates where appropriate.
• Support rolling updates as new parts lists, procurement records, and supplier information become available.
• Translate user needs into practical data products and explain the limitations of the underlying data.

Minimum qualifications

• Experience integrating, transforming, and analyzing data from multiple sources.
• Proficiency in SQL and Python or comparable data processing tools.
• Experience designing structured datasets, data pipelines, and quality assurance checks.
• Ability to resolve inconsistent identifiers and document matching methods and exceptions.
• Experience producing analytical outputs that can be reviewed and used by nontechnical stakeholders.
• Strong collaboration and communication skills, including the ability to work with subject matter experts.
• Ability to document assumptions, data provenance, and analytical limitations.

Preferred qualifications

• Experience with defense logistics, procurement, inventory, or supplier datasets.
• Familiarity with NSNs/NIINs, CAGE codes, bills of materials, and assembly hierarchies.
• Experience with entity resolution, graph analysis, or supply network mapping.
• Experience developing lead-time, capacity, or schedule models in partnership with domain experts.

The target salary range for this position is $108,301 - $160,653.79.

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.

Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.

Job Locations

US-Remote US-VA-Tysons