Cleared Data Engineer (5786)

SMX

1d•$115,000 - $187,000

About The Position

SMX is hiring a Data Engineer to design, build, and optimize systems for data collection, storage, access, and analytics at scale. The role analyzes and organizes raw data, builds robust data systems, and improves data quality and reliability. It collaborates with analytics and business teams to turn data from multiple sources into high-quality, accessible data pipelines. The position creates pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other consumers; makes data available, accessible, and secure to stakeholders; and ensures pipelines meet service-level agreements and performance standards. It also monitors data repositories and pipelines for operational efficiency, resolves problems, and implements orchestration and automation solutions for data pipelines. The proposed salary range is $115,000–$187,000 USD. SMX offers health insurance, paid leave, retirement, and learning and development opportunities. The selected applicant may be subject to a background investigation and/or education verification. SMX does not provide immigration-related employment authorization support for this position.

Requirements

Bachelor's degree in computer science, information technology, data engineering, or a related field.
Eight 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 written and verbal communication skills, with the ability to interface with customers.

Nice To Haves

Experience supporting AI/ML pipelines, vectorization, or embedding generation.
Experience with data governance, access controls, or sensitive data protection.
Exposure to DevOps/CI-CD patterns for data workflows.
Experience with Databricks.
Experience with real-time data streaming and event-driven architectures.

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 solutions for data pipelines.