Senior Data Engineer

• Design, build, and maintain reliable, high-volume data pipelines and ETL processes.
• Develop and optimize complex SQL queries for analytics, reporting, and application support.
• Implement robust data architectures using star schemas, fact tables, and dimension tables.
• Process massive datasets efficiently using Apache Spark and the Hadoop ecosystem.
• Build and manage real-time streaming pipelines using Kafka.
• Leverage AWS services — S3, EMR, Redshift, DynamoDB — for storage and processing.
• Automate workflows with bash scripting.
• Use Python to support various data engineering tasks as needed.
• Collaborate with analysts, engineers, and stakeholders to deliver secure, reliable data solutions.
• (Nice to have) Work with Databricks and delta tables for advanced analytics.
  
   

Must-Have Skills — No Exceptions

Candidates must have ALL of the following:

 

• Minimum of 7 years of professional data engineering experience.
• U.S. Citizenship and proof you currently hold or have previously held a minimum of a Public Trust clearance.
• Commitment to work onsite in Ashburn, VA 2–3 days per week (non-negotiable).
• Strong Java programming experience in production.
• Advanced SQL skills with a track record of performance tuning on large datasets.
• Proficiency in bash scripting for automation.
• Extensive AWS experience — S3, EMR, Redshift, DynamoDB.
• Strong understanding of star schemas and data warehousing best practices.
• Proven experience with Apache Spark and the Hadoop ecosystem.
• Hands-on experience with Kafka for real-time streaming pipelines.
• Demonstrated success building and maintaining production-grade data pipelines.
• Proficiency with Python.
• B.S. or M.S. in Computer Science, Engineering, or related field