HR Data Engineer: AI-Driven Data Pipelines

PDS Defense, Inc.; Herndon (VA); Hybrid; USD 95,000 - 125,000; Full time

Benefits offered by this job

Direct deposit

401(k)

Career counseling services

Paid holidays

Short-term disability insurance

Skills training

Employee referral bonus

Affordable medical coverage

Job summary

PDS Defense, Inc. is seeking an HR Data Engineer in Herndon, VA. The role focuses on building and optimizing HR data pipelines, transforming raw data into useful HR analytics, and delivering robust data architectures to support AI agents.

You will design and maintain ETL pipelines, integrate with core business systems, and ensure data quality through testing and governance. A strong background in SQL, Python and data engineering is essential.

Qualifications

• Bachelor's degree in Business Information Technology, MIS, CS, IT, Economics, Math, Data Science/Analytics, Eng or equivalent.
• 2 years of SQL and Python experience.
• Experience building ETL pipelines using code or ETL platforms.
• Experience designing scalable data architectures for AI agent data needs.
• Certification in Data Engineering (e.g., Google Cloud Professional Data Engineer) preferred.

Responsibilities

• Design and build data sets, big data pipelines, and architectures.
• Develop, deploy, and monitor agentic workflows that automate HR data tasks.
• Create scalable data architectures for AI training, deployment, and operation.
• Automate processes to reduce manual data entry and improve data delivery.
• Ingest data from multiple sources and maintain data pipelines.

Skills

SQL

Python

ETL pipelines

Data architectures

API design

Education

Bachelor's degree in IT/CS/Analytics

Tools

APIs

ETL platforms

Data pipelines tooling

Job description

PDS Defense, Inc. is seeking an HR Data Engineer in Herndon, VA. The role focuses on building and optimizing HR data pipelines, transforming raw data into useful HR analytics, and delivering robust data architectures to support AI agents.

You will design and maintain ETL pipelines, integrate with core business systems, and ensure data quality through testing and governance. A strong background in SQL, Python and data engineering is essential.