Secret-Cleared Data Engineer: Scalable ETL & Pipelines

SMX; Madison (WI); On-site; USD 115,000 - 187,000; Full time

Benefits offered by this job

Health insurance

Retirement

Paid leave

Job summary

SMX is seeking a Data Engineer to design, build, and optimize data systems for collection, storage, access, and analytics at scale. The role involves transforming raw information from diverse sources into high-quality, accessible data pipelines that support analytics and data-centric applications.

The ideal candidate will analyze and organize raw data, build robust data systems, and collaborate with analytics and business teams to improve data quality, governance, and reliability.

Qualifications

• Bachelor's degree in computer science, information technology, data engineering, or a related field.
• 8 years of professional experience in data engineering or backend software engineering.
• Active Secret security clearance.
• Strong proficiency in SQL and data query creation.
• Experience with data modeling, data migration, and ETL functions.
• Excellent communication skills, both written and verbal, with the ability to interface with customers.

Responsibilities

• Create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers
• Make data available, accessible, and secure to stakeholders.
• Ensure data pipelines meet Service Level Agreements and performance standards
• Monitor data repositories and data pipelines to ensure operational efficiency and take action to address and resolve problems
• Implement orchestration and automation solution for data pipelines

Skills

SQL proficiency

Data modeling

ETL processes

Communication skills

Backend software engineering

Education

Bachelor's degree in CS/IT/Data Eng or related

Tools

Databricks

CI/CD for data workflows

DevOps patterns

Job description

SMX is seeking a Data Engineer to design, build, and optimize data systems for collection, storage, access, and analytics at scale. The role involves transforming raw information from diverse sources into high-quality, accessible data pipelines that support analytics and data-centric applications.

The ideal candidate will analyze and organize raw data, build robust data systems, and collaborate with analytics and business teams to improve data quality, governance, and reliability.