Cleared Data Engineer - Secure Pipelines & ETL

SMX; Hagåtña (GU); On-site; USD 115,000 - 187,000; Full time

Benefits offered by this job

Health insurance

Paid leave

Retirement plan

Job summary

SMX is hiring a Data Engineer to design, build, and optimize data systems for data collection, storage, access, and analytics at scale. You will analyze and organize raw data, build robust data pipelines, and collaborate with analytics and business teams to transform raw information into high-quality, accessible data for data science and applications.

The role focuses on creating pipelines, ensuring data accessibility and security for stakeholders, meeting SLAs, monitoring pipelines for

Qualifications

• Bachelor's degree in CS/IT/Data Eng or related field.
• 8 years of professional data engineering or backend software experience.
• Active Secret security clearance.
• Strong SQL and data query proficiency.
• Experience with data modeling, migration and ETL.
• Excellent written and verbal communication with customers.

Responsibilities

• Create data pipelines that convert raw data into formats usable by data scientists and data-centric applications.
• Make data available, accessible, and secure to stakeholders.
• Ensure data pipelines meet SLAs and performance standards.
• Monitor data repositories and pipelines to maintain operational efficiency and address issues.
• Implement orchestration and automation solutions for data pipelines.

Skills

SQL proficiency

Data streaming

DevOps/CI-CD

AI/ML pipelines

Communication

Data migration

ETL

Databricks

Education

Bachelor's degree in computer science, information technology, data engineering, or a related field

Active Secret security clearance

Tools

Databricks platform

Job description

SMX is hiring a Data Engineer to design, build, and optimize data systems for data collection, storage, access, and analytics at scale. You will analyze and organize raw data, build robust data pipelines, and collaborate with analytics and business teams to transform raw information into high-quality, accessible data for data science and applications.

The role focuses on creating pipelines, ensuring data accessibility and security for stakeholders, meeting SLAs, monitoring pipelines for