Data Engineer IRS MBI Clearance

Washington, United States | Posted on 01/11/2026

We are seeking an experienced Data Engineer to design, build, and maintain scalable data processing pipelines using modern big data technologies. The ideal candidate will have strong development skills and experience with distributed computing frameworks.

• Bachelor's degree in Computer Science, Engineering, or related technical field
• 5+ years of software development experience
• Strong proficiency in Python, Java or Scala programming languages
• Hands on Experience working with cloud-based Spark platforms (Databricks, AWS EMR, AWS Glue)
• Strong understanding of Hive, Unity catalog, Glue catalog
• Hands on Experience working with any data quality framework/tools
• Hands on Experience working with Observability and monitoring for data processing pipelines
• Strong understanding of distributed computing concepts
• Proficiency in version control systems (Github/Git Lab/Bitbucket)

• Spark SQL
• Spark Streaming and its data sources KAFKA, CDC feed, etc
• Performance optimization and tuning
• Data transformation and processing

• Experience building and maintaining high-volume data processing pipelines
• Knowledge of data modeling and ETL / ELT best practices
• Familiarity with SQL and No
  
  SQL databases
• Understanding of data warehouse concepts and dimensional modeling

• Experience with real-time data processing and streaming architectures
• Knowledge of Delta Lake or similar data lakehouse technologies
• Experience with CI/CD pipelines
• Contributions to open-source projects

• Design and implement scalable data pipelines
• Optimize existing data workflows for performance and reliability
• Collaborate with data scientists and analysts to support their data needs
• Implement data quality checks and monitoring
• Maintain documentation for data processes and architectures

• Strong problem-solving abilities
• Team collaboration
• Ability to work independently
• Strong attention to detail

The ideal candidate should have a proven track record of developing and maintaining production-grade data pipelines and be passionate about working with large-scale data systems.