JOB SUMMARY:

The Mid-Level Data Engineer will play a crucial role in the DoD team, focusing on building and maintaining data pipelines and architectures that support the development of AI-enabled applications and analytics solutions. This position is essential for ensuring the effective integration and management of data across various platforms to enhance decision-making capabilities within the Department of Defense (DoD).

Key Responsibilities:

• Data Pipeline Development: Design, implement, and optimize data pipelines to ingest, process, and store diverse datasets from multiple sources, ensuring high availability and reliability.
• Data Integration: Collaborate with data scientists, analysts, and other engineers to integrate data from various systems into a cohesive architecture that supports advanced analytics and machine learning initiatives.
• Performance Monitoring: Monitor data processing workflows to ensure optimal performance and troubleshoot any issues that arise in the data pipeline.
• Data Quality Assurance: Implement data quality checks and validation processes to maintain the integrity and accuracy of data used in analytics.
• Documentation: Develop and maintain comprehensive documentation for data architectures, processes, and workflows to facilitate knowledge sharing within the team.

Skills Required:

• Education: Bachelor’s degree in computer science, Data Engineering, Information Technology, or a related field; master’s degree preferred.
• Clearance Requirements: Active Top Secret (TS) clearance with Sensitive Compartmented Information (SCI) eligibility
• Minimum of 5 years of experience in data engineering or a related field with a focus on building data pipelines and architectures.
• Proven experience with big data technologies such as Apache Spark, Hadoop, or similar frameworks.
• Familiarity with cloud platforms (e.g., AWS, Azure) for data storage and processing is advantageous.
• Proficiency in programming languages such as Python, Java, or Scala; experience with SQL for database management.
• Strong understanding of data modeling concepts and best practices for managing large datasets.
• Excellent problem-solving skills with the ability to analyze complex data issues.

Benefits:

• Comprehensive Medical, Dental, and Visions Plans (Healthcare benefits are 100% employer-paid for employees only)
• Life Insurance
• Paid Time Off (Flexible/Combined PTO, Bereavement Leave, 11 Company Paid Holidays)
• 401K Retirement Plan with employer match
• Professional Development Training Reimbursement
• Flexible/remote work schedules

Salary range: $110,000 - $120,000.
ZbrpiS5Rc

• Data Pipeline Development: Design, implement, and optimize data pipelines to ingest, process, and store diverse datasets from multiple sources, ensuring high availability and reliability.
• Data Integration: Collaborate with data scientists, analysts, and other engineers to integrate data from various systems into a cohesive architecture that supports advanced analytics and machine learning initiatives.
• Performance Monitoring: Monitor data processing workflows to ensure optimal performance and troubleshoot any issues that arise in the data pipeline.
• Data Quality Assurance: Implement data quality checks and validation processes to maintain the integrity and accuracy of data used in analytics.
• Documentation: Develop and maintain comprehensive documentation for data architectures, processes, and workflows to facilitate knowledge sharing within the team