Secret-Cleared Data Engineer - Data Pipelines & Analytics

SMX; Lansing (MI); Presencial; USD 115.000 - 187.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Paid leave

Retirement

Descripción de la vacante

SMX is hiring a Data Engineer to design, build, and optimize systems for data collection, storage, access, and analytics at scale. The ideal candidate will analyze and organize raw data, build robust data systems, and transform information from diverse sources into high‑quality, accessible data pipelines for data scientists and business teams.

Responsibilities include creating pipelines, ensuring data availability and security, monitoring performance, and implementing orchestration for data

Formación

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

Responsabilidades

• Create data pipelines converting raw data for data scientists and apps.
• Make data available, accessible, and secure to stakeholders.
• Ensure pipelines meet SLAs and performance standards.
• Monitor data repositories and pipelines for efficiency and issue resolution.
• Implement orchestration and automation for data workflows.

Conocimientos

8+ years data eng

SQL

Data modeling

ETL

Security clearance

Communication skills

AI/ML pipelines

Data governance

DevOps/CI-CD for data

Real-time streaming

Educación

Bachelors in CS/IT/Data Eng

Herramientas

Databricks

Descripción del empleo

SMX is hiring a Data Engineer to design, build, and optimize systems for data collection, storage, access, and analytics at scale. The ideal candidate will analyze and organize raw data, build robust data systems, and transform information from diverse sources into high‑quality, accessible data pipelines for data scientists and business teams.

Responsibilities include creating pipelines, ensuring data availability and security, monitoring performance, and implementing orchestration for data