Data Engineer

at  10x National Security

JOB SUMMARY

We are seeking a skilled Data Engineer to join our dynamic team. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and architectures that enable efficient data storage and retrieval. This role requires a strong analytical mindset and the ability to work collaboratively with cross-functional teams to support data-driven decision-making processes.

SKILLS

• Proficiency in SQL for database querying and management.
• Experience with AWS cloud services for scalable data solutions.
• Familiarity with database design principles and best practices.
• Knowledge of analytics tools and methodologies to derive insights from complex datasets.
• Ability to work with linked data concepts to enhance data usability across different systems.
• Strong problem-solving skills with a focus on optimizing performance in data processing tasks.
  Join us in leveraging your expertise in data engineering to drive impactful insights that shape our business strategies!
  Job Type: Full-time
  Pay: $107,696.00 - $185,130.00 per year

Benefits:

• 401(k)
• 401(k) matching
• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Vision insurance

Compensation Package:

• Bonus opportunities

Security clearance:

• Secret (Required)

Ability to Commute:

• Hanover, MD 21076 (Preferred)

Ability to Relocate:

• Hanover, MD 21076: Relocate before starting work (Required)

Work Location: Hybrid remote in Hanover, MD 2107

• Design and implement robust data models and architectures to support business intelligence initiatives.
• Develop, construct, test, and maintain data architectures, including databases and large-scale processing systems.
• Collaborate with data scientists and analysts to understand data requirements and deliver high-quality datasets.
• Optimize SQL queries for performance improvements in data retrieval processes.
• Utilize AWS services for cloud-based data solutions and storage management.
• Implement linked data strategies to enhance data interoperability across platforms.
• Monitor system performance and troubleshoot issues related to data processing workflows.
• Document processes, data models, and architectural designs for future reference.