Data Engineer — AI/ML Pipelines for National Security

Ignite Digital; Charleston (AR); On-site; USD 86,000 - 105,000; Full time

Benefits offered by this job

Competitive pay

Education stipends

Referral bonuses

Work with US government

Volunteer opportunities

Growth opportunities

Job summary

Ignite Digital in the United States seeks a Data Engineer to design, implement, and optimize data systems and pipelines that enable AI/ML applications for a Navy IT command. You will collaborate with AI/ML engineers and technical teams to ensure scalable, reliable data processing and secure data workflows.

The role applies modern data engineering practices to support mission‑critical analytics, improve data quality, and align with enterprise data architectures across the client’s IT ecosystem.

Qualifications

• 5 years in data management and analysis for corporate operations.
• 3 years BI experience designing dashboards, reporting solutions, and integrations using QLIK Advana.
• Experience designing varied data visualization techniques for different audiences.
• Experience with project planning, milestones, risk, cross-functional collaboration, and stakeholder communication.
• Technical skills: Python, SQL, data modeling, APIs, data architecture.
• Knowledge and skill with AI libraries.

Responsibilities

• Analyze use cases and refine data solution requirements.
• Define data architectures, standards, transformations, and integrations.
• Publish and maintain reference materials for analysts and consumers.
• Provide automation through modern software-intensive solutions.

Skills

Python

SQL

Data modeling

APIs

Data architecture

AI libraries

Education

BS degree in a related field

Tools

QLIK Advana

Job description

Ignite Digital in the United States seeks a Data Engineer to design, implement, and optimize data systems and pipelines that enable AI/ML applications for a Navy IT command. You will collaborate with AI/ML engineers and technical teams to ensure scalable, reliable data processing and secure data workflows.

The role applies modern data engineering practices to support mission‑critical analytics, improve data quality, and align with enterprise data architectures across the client’s IT ecosystem.