Hiring.Camp

Technical Lead – Data Operations - Clearance Required

Lmi

·

Today

Salary
$122k – $211k
Location
Tysons, VA, US
Workplace
Remote, Hybrid, Onsite
Type
Full-time
Department
IT
Seniority
Lead
Experience
2+ years
Clearance
Required
Closing date
Today
Source
iCIMS

Description

Overview

LMI is seeking a skilled Data Operations Technical Lead to organize and lead a team of data scientists/engineers in the performance of data architecture/ingestion activities for a technology-enabled supply chain risk management platform for the Department of War. Successful candidates demonstrate competency in logistics, data analysis, leading teams, executive engagement, and business development. This is a hybrid work opportunity offering a combination of telework and onsite client work.

 

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

  • Lead and mentor a team of data scientists, data engineers, and data analysts supporting a technology-enabled supply chain risk management platform for the Department of War.
  • Architect, implement, and maintain end-to-end data pipelines for ingestion, transformation, validation, and storage of large, complex logistics and supply chain datasets.
  • Own version-controlled data pipeline development using Git, ensuring all ETL/ELT code, schemas, and configurations follow strict branching, peer review, and CI/CD deployment standards.
  • Define and enforce data management standards, including data models, metadata, data dictionaries, lexicons, and business rules to ensure consistency and interoperability.
  • Design, implement, and oversee AI/ML solutions (e.g., predictive risk models, anomaly detection, forecasting) to derive actionable insights from structured and unstructured data.
  • Implement and manage data quality frameworks and metrics, including validation and verification testing, to ensure accuracy, completeness, and timeliness of data.
  • Collaborate with cross-functional teams (product, cyber, DevSecOps, platform engineering, logistics SMEs) to translate mission and business needs into scalable technical data solutions.
  • Lead the design and optimization of data infrastructure (databases, data lakes, cloud services, cross-domain solutions) to support high-performance analytics and AI/ML workloads.
  • Perform in-person and virtual demonstrations of the technology-enabled supply chain risk management platform to internal and external stakeholders.

Qualifications

MINIMUM QUALIFICATIONS:

  • Bachelor’s degree in computer science, data science, information systems, engineering, operations research, logistics, or a related field; equivalent experience considered.
  • Proven experience (typically 5+ years) in data engineering, data science, or data architecture roles, with at least 2 years in a technical lead or team leadership position.
  • Demonstrated experience designing, building, and operating data pipelines and architectures using modern ETL/ELT tools, cloud platforms (e.g., AWS, Azure, GCP), and distributed data systems.
  • Strong hands-on proficiency with SQL and at least one programming language commonly used for data (e.g., Python, R, Scala), including experience integrating AI/ML models into production workflows.
  • Experience applying Agile methodologies and DevSecOps practices to data and analytics projects, including CI/CD workflows, automated testing, and infrastructure-as-code where applicable.
  • Direct experience working with logistics, supply chain, intelligence, transportation, or related domains; familiarity with supply chain risk management concepts and metrics.
  • Demonstrated ability to engage with senior/executive stakeholders, communicate complex technical concepts clearly, and translate mission needs into technical requirements and roadmaps.
  • Knowledge of and experience with data governance, data quality management, metadata management, and implementing security and privacy controls in accordance with DoD or federal standards.
  • Active Secret Security Clearance.

DESIRED SKILLS

  • Master’s degree in computer science, data science, information systems, engineering, operations research, logistics, or a related field.
  • Prior military or DoD civilian/contractor experience. 
  • Working knowledge of War Data Platform or its underlying technology (Databricks, etc).
  • Experience leveraging various DoD supply chain datasets to conduct supply chain risk analysis.
  • Located in the National Capital Region.
  • Active Top Secret Security Clearance.

The target salary range for this position is $122,000-$211,000. 

 

#LI-SH1

 

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-VA-Tysons

Skills

PythonScalaAWSAzureGCPCI/CDSQLDatabricksData ScienceData EngineeringETLGitAgileRisk ManagementR

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