Cleared Data Engineer: Secure, Scalable Data Pipelines

SMX; Atlanta (GA); On-site; USD 115,000 - 187,000; Full time

Benefits offered by this job

Health insurance

Paid leave

Retirement plan

Job summary

SMX is seeking a Data Engineer to design, build, and optimize data pipelines for scalable data collection, storage, access, and analytics. The role focuses on transforming raw data from diverse sources into high-quality, accessible datasets for data scientists and business teams.

You will collaborate with analytics and product teams, ensure data quality and security, and implement orchestration for ETL workflows, while maintaining SLA targets and operational efficiency.

Qualifications

• Bachelor's degree in computer science, information technology, data engineering, or a related field.
• 8 years of professional experience in a data engineering or backend software engineering role.
• 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

Strong communication

Secure data practices

Backend software engineering

Education

Bachelor's degree in Computer Science/IT/Data Engineering

Active Secret security clearance

Tools

Databricks

Job description

SMX is seeking a Data Engineer to design, build, and optimize data pipelines for scalable data collection, storage, access, and analytics. The role focuses on transforming raw data from diverse sources into high-quality, accessible datasets for data scientists and business teams.

You will collaborate with analytics and product teams, ensure data quality and security, and implement orchestration for ETL workflows, while maintaining SLA targets and operational efficiency.