Energy Data Analytics Lead - Logistics Management Institute

Overview

LMI is seeking a skilled Energy Data Analytics Lead focused on infrastructure, energy, and environment data and tools. Successful candidates demonstrate competency in data pipelining, data analysis, statistics, programming, project execution, tool development and optimization, and critical thinking paired with functional knowledge of infrastructure, energy, or environment data.

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

• Support a major civilian federal agency while leading data engineering initiatives across LMI as needed.
• Optimize and modernize data pipelines to improve performance, scalability, and long-term sustainability.
• Design and develop new data tools and solutions to support reporting, analytics, and business needs.
• Serve as the lead Data Architect, driving tool development, solution implementation, and innovation across the division.
• Apply functional knowledge of energy-related operations to inform architecture, analytics, and solution design.

Qualifications

Required:

• Bachelor’s degree in data science, mathematics, statistics, economics, computer science, engineering, or a related business or quantitative discipline.
• Broad working familiarity with data analysis, automation, dashboards, databases, cloud data tools, APIs, and lightweight application or scripting approaches.
• Experience using technical tools such as Python, JavaScript, Google Apps Script, SQL, BI platforms, or cloud data services to improve reporting, analysis, or operational workflows.
• Working knowledge of data pipelines and data transformation concepts, including data ingestion, validation, reconciliation, refresh processes, and documentation.
• Ability to evaluate existing tools and workflows, identify technical risks or inefficiencies, and recommend practical improvements across multiple possible technological approaches.
• Ability to coordinate with analysts, developers, data engineers, and non-technical stakeholders to scope requirements, compare solution options, and support implementation.
• Ability to explain technical work in c