Senior Data Engineer - Secure, Scalable Pipelines

SMX; Phoenix (AZ); 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 systems for data collection, storage, access, and analytics at scale. You will transform raw information from various sources into high-quality, accessible data pipelines and collaborate with analytics and business teams.

The role requires analyzing data, building robust data systems, and enhancing data quality and reliability. You will work with data engineers, data scientists, and stakeholders to ensure reliable data delivery across

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 usable formats for data scientists and other data consumers.
• 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 problems.
• Implement orchestration and automation solutions for data pipelines.

Skills

SQL proficiency

Data modeling

ETL processes

Security clearance

Education

Bachelor's degree

Tools

Databricks

CI/CD for data workflows

Job description

SMX is seeking a Data Engineer to design, build, and optimize systems for data collection, storage, access, and analytics at scale. You will transform raw information from various sources into high-quality, accessible data pipelines and collaborate with analytics and business teams.

The role requires analyzing data, building robust data systems, and enhancing data quality and reliability. You will work with data engineers, data scientists, and stakeholders to ensure reliable data delivery across