Databricks Data Engineer and Scientist

Parra Consulting Group, Inc. . • Gaithersburg, MD

1d

About The Position

Parra Consulting Group (PCG) is seeking a Databricks Data Engineer and Scientist to support a federal client’s critical enterprise Lakehouse. The role designs, builds, and maintains robust data pipelines and applies data science, AI, and analytics skills to turn raw data into actionable business insights. The successful candidate will work with Databricks and AWS, develop and manage ETL processes, design data models within a Bronze, Silver, and Gold medallion architecture, optimize pipeline performance, and help ensure data security and compliance. The position also involves analyzing and rebuilding complex legacy SQL-based pipelines and models, validating results, and collaborating with cross-functional teams to deliver analytics-ready data.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Engineering, Math, Physics, or Information Systems and Technology.
• 8+ years of experience designing, developing, deploying, and managing ETL processes and data pipelines.
• Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
• U.S. citizenship required to support this federal contract.
• 3+ years of experience building, debugging, and optimizing data pipelines using Databricks notebooks, clusters, and job orchestration tools, including Delta Lake and Unity Catalog.
• 3+ years of experience writing Python and PySpark code for ETL scripts and custom transformations.
• Experience designing, developing, deploying, and managing ETL processes and data pipelines with comprehensive logging and error handling.
• Experience using AI-assisted coding tools, such as Claude Code or Cursor, for data engineering and data modeling tasks.
• Experience with data modeling, including selecting dimensional or relational models within a Bronze, Silver, and Gold medallion architecture.
• Experience using AWS services, including AWS Glue, Amazon S3, and Amazon RDS.
• Knowledge of ETL performance optimization techniques, such as partitioning, bucketing, and caching, and experience troubleshooting query performance.
• Ability to analyze and decompose complex legacy SQL, rebuild data pipelines or models, and compare results to validate accuracy and performance.

Responsibilities

• Design, build, and maintain end-to-end data pipelines for an enterprise Lakehouse on Databricks and AWS.
• Develop and manage ETL processes with comprehensive logging and error handling, and troubleshoot and resolve issues.
• Design data models within a Bronze, Silver, and Gold medallion architecture, selecting dimensional or relational approaches as appropriate.
• Analyze and decompose complex legacy SQL, rebuild pipelines and models, and compare results to validate accuracy and performance.
• Optimize pipeline performance and scalability using techniques such as partitioning, bucketing, and caching.
• Use AI-assisted coding tools to support pipeline analysis, data engineering, and data modeling tasks.
• Help ensure data security and compliance.
• Collaborate with cross-functional teams to deliver analytics-ready data.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior