Data Engineer

Razor is seeking an experienced Data Engineer to support an Artificial Intelligence initiative within a multidisciplinary and collaborative project environment. This role will focus on developing and maintaining data pipelines, performing complex data analysis, and preparing data to support AI and Machine Learning development across multiple environments and classification levels.
The Data Engineer will work closely with project leadership, technical teams, customers, and vendors to coordinate data requirements, improve data processes, and ensure reliable delivery of datasets supporting mission-critical AI initiatives.

Education Requirements:

• Bachelor's degree in Data Engineering, Data Science, Information Management, Computer Science, Engineering, or a related field.

Clearance Requirements:

• Must be a U.S. Citizen.
• Ability to obtain and maintain a TS/SCI clearance with Polygraph is required.

Location & Work Arrangement:

• Primary customer location: Springfield, Virginia
• Company office: Fairfax, Virginia
• Hybrid work arrangement requiring a minimum of 3 business days onsite, with the potential for up to 5 days onsite depending on program and mission requirements.
• Work may include support within classified customer environments.

Responsibilities:

• Develop, maintain, optimize, and automate data pipelines supporting AI and Machine Learning initiatives.
• Extract, transform, and load data for ingestion into Machine Learning development environments.
• Develop and document data workflows, procedures, and data-management best practices across multiple environments and classification levels.
• Participate in technical exchange meetings with customers, vendors, and internal teams to coordinate, prioritize, and track datasets supporting AI efforts.
• Coordinate with the Program Manager and Data Team to identify data requirements and serve as a project data advocate.
• Perform complex data analysis and communicate results to customers in a clear and actionable manner.
• Parse and transform data in multiple formats for Machine Learning applications.
• Identify, document, and independently address technical challenges.
• Identify and implement process improvements to optimize data delivery and automate manual processes.
• Perform root cause analysis across internal and external processes to identify opportunities for improvement.
• Collaborate with project stakeholders and technical teams to support successful AI/ML development efforts.

Required Qualifications:

• 2-8+ years of experience in Data Engineering, Computer Engineering, Computer Science, Data Science, or a related technical area.
• Advanced proficiency with Python, PySpark, and/or SQL.
• Advanced experience parsing and preparing data in different formats for Machine Learning applications.
• Strong experience with text parsing.
• Advanced knowledge of database principles and technologies.
• Strong data-processing and data-transformation skills.
• Experience building, optimizing, and automating data pipelines.
• Ability to perform root cause analysis and identify opportunities for process improvement.
• Strong analytical, problem-solving, and communication skills.
• Ability to work effectively within collaborative, multidisciplinary technical teams.

Preferred Qualifications:

• Experience with Databricks or similar data-management platforms.
• Experience supporting Artificial Intelligence and Machine Learning development, particularly computer vision.
• Experience with cloud technologies such as Amazon Web Services (AWS) or Microsoft Azure.
• Experience working with a variety of geospatial data formats.

Razor is an EEO Employer
Razor is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic.
Razor Benefits Overview
Razor offers a comprehensive benefits package that may include medical, dental, and vision insurance; life and disability insurance; paid time off and holidays; a 401(k) plan; and professional development opportunities. Benefits offerings may vary based on position and employment status.