Databricks Data Engineer, Lead

Booz Allen Hamilton•Bethesda, MD

1d•$77,600 - $176,000

About The Position

As a lead Databricks Data Engineer, you will be hands-on designing, building, and maintaining robust data pipelines within Databricks and contributing independently while also providing technical leadership and mentorship within the team. Your key responsibilities will include creating and optimizing end-to-end data flows, handling extract, transform, load (ETL) processes, designing data models, ensuring data security and compliance, collaborating with cross-functional teams, and continuously improving performance and scalability. Your experience in both Databricks and AWS environments and services will position you as a technical team leader. Your expertise will bridge the gap between raw data and actionable insights, enabling efficient data processing and analytics across the business. Here, you’ll mentor a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. You’ll use your expertise in analytical exploration and data examination while you oversee the assessment, design, building, and maintenance of scalable platforms for your clients. Work with us to use data for good. Join us. The world can’t wait.

Requirements

8+ years of experience designing, developing, deploying, and managing ETL processes and data pipelines utilizing comprehensive logging and robust error handling mechanisms to troubleshoot and resolve issues
3+ years of experience building, debugging, and optimizing data pipelines using Databricks notebooks, clusters, and job orchestration tools using Databricks tools such as Delta Lake, Databricks Delta, and Unity Catalog
3+ years of experience writing Python and PySpark code for ETL scripts and custom transformations
Experience in data modeling, including when to use dimensional vs relation data models within a medallion architecture, including Bronze, Silver, or Gold
Experience using various AWS services, including AWS Glue, Amazon S3, Amazon RDS
Knowledge of performance optimization techniques for ETL jobs such as partitioning, bucketing, caching, and troubleshooting to improve query performance
Ability to design and implement data models from initially defining schemas to optimizing data structures that support efficient queries and analytics
Public Trust determination is required
Bachelor’s degree in Computer Science, Computer Engineering, Engineering, Mathematics, Physics, Information Systems, or Information Technology

Nice To Haves

Experience with AWS cloud-native data services such as AWS Lambda or CloudWatch that support serverless architectures for data processing
Experience with tools such as AWS Glue Data Catalog or Collibra for managing metadata, data lineage, and cataloging data assets
Knowledge of data governance practices, data lineage, and compliance requirements, including GDPR or CCPA, in support of data quality, privacy, and security
Ability to explain complex technical concepts to a non-technical audience, including describing tradeoffs in architectural design

Responsibilities

Creating and optimizing end-to-end data flows
Handling extract, transform, load (ETL) processes
Designing data models
Ensuring data security and compliance
Collaborating with cross-functional teams
Continuously improving performance and scalability
Mentoring a multi-disciplinary team of analysts, data engineers, developers, and data consumers
Overseeing the assessment, design, building, and maintenance of scalable platforms