Job Openings >> Databricks Data Engineer (Top Secret Clearance) - US Citizens Only
Databricks Data Engineer (Top Secret Clearance) - US Citizens Only
Summary
Title:Databricks Data Engineer (Top Secret Clearance) - US Citizens Only
ID:5331
Location:USA
Department:Information Technology
Description

Only U.S. Citizens with Top Secret Clearance should apply.
FIDES is looking for a Data Engineer with an active Top Secret Clearance and prior Databricks experience.

The Databricks Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and infrastructure. The successful candidate will have a solid foundation in data engineering principles, substantial experience with Databricks, and a proven track record of implementing robust data solutions. Responsibilities for this role include:

  • Collaborate with cross-functional teams to understand data requirements and design appropriate solutions using Databricks.
  • Develop and maintain efficient ETL pipelines to ingest, process, and transform large volumes of data.
  • Implement data quality checks and monitoring processes to ensure data integrity and reliability.
  • Optimize and tune Databricks clusters for performance and scalability.
  • Work closely with data scientists and analysts to support their data needs and enable advanced analytics.

Requirements

  • Bachelor's degree in Computer Science, Engineering, or related field.
  • 3-5 years of experience in data engineering and big data technologies.
  • Active Top Secret (TS) clearance with SCI eligibility. 
  • Experience supporting the Department of Defense (DoD) or Intelligence Community (IC).
  • Proficiency with Databricks, Python, and SQL.
  • Strong knowledge of data warehousing concepts and best practices.
  • Hands-on experience deploying and maintaining data pipelines using Databricks or similar tools.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.

Preferred Qualifications

  • Certification in Databricks and other relevant certifications.
  • Experience with other big data technologies such as Apache Spark, Hadoop, or Kafka.
  • Knowledge of containerization technologies such as Docker and Kubernetes.
  • Experience with version control systems such as Git.
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