Cleared Data Engineer — Scalable Pipelines & AI-Ready

SMX; Carson City (NV); On-site; USD 115,000 - 187,000; Full time

Benefits offered by this job

Health insurance

Paid leave

Retirement

Job summary

SMX is hiring a Data Engineer to design, build, and optimize data systems for data collection, storage, access, and analytics at scale. The ideal candidate will analyze and organize raw data, build robust data systems, and explore ways to enhance data quality and reliability.

This role involves collaborating with analytics and business teams to transform raw information from different sources into high-quality, accessible data pipelines.

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 functions

Communication skills

Security clearance

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

Job description

SMX is hiring a Data Engineer to design, build, and optimize data systems for data collection, storage, access, and analytics at scale. The ideal candidate will analyze and organize raw data, build robust data systems, and explore ways to enhance data quality and reliability.

This role involves collaborating with analytics and business teams to transform raw information from different sources into high-quality, accessible data pipelines.