Staff Data Engineer (TS/SCI) - AI/ML Data Architect

TSG; King of Prussia (PA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Relocation assistance

Flexible scheduling

HSA contributions

401k plan

Vacation and holidays

Tuition assistance

Performance bonus

Life insurance and AD&D

Parental leave

Employee assistance program

Job summary

ARKA Group L.P. is seeking a Staff Data Engineer/Scientist to lead the development of ETL pipelines for AI/ML and LLM solutions.

You will mentor an interdisciplinary team of developers and researchers while building scalable data infrastructure to support a broad set of customer challenges. The role requires a minimum of six years in data engineering/science, a TS/SCI clearance with Full Scope Polygraph, and hands-on experience with Python data tools and modern DevOps practices.

Qualifications

• B.S. in data science, AI/ML, computer science, or related field
• Minimum six years of experience as a Data Engineer/Scientist
• Experience developing data pipelines and normalizing data with NumPy, Pandas, Polars
• Experience with version control (GitLab, Git, Bitbucket)
• Active TS/SCI U.S. Government Security Clearance with a Full-Scope Polygraph (FSP)

Responsibilities

• Lead and mentor an interdisciplinary team of developers and researchers
• Build ETL pipelines to support AI/ML and LLM solutions
• Assemble large, complex data sets to support AI/ML algorithms
• Create infrastructure for ETL data from diverse sources
• Identify improvements to increase scalability and automate processes
• Develop software using Agile methodologies

Job description

ARKA Group L.P. is seeking a Staff Data Engineer/Scientist to lead the development of ETL pipelines for AI/ML and LLM solutions.

You will mentor an interdisciplinary team of developers and researchers while building scalable data infrastructure to support a broad set of customer challenges. The role requires a minimum of six years in data engineering/science, a TS/SCI clearance with Full Scope Polygraph, and hands-on experience with Python data tools and modern DevOps practices.