Data Engineer, Senior

Booz Allen Hamilton•Washington, DC

1d•$99,000 - $225,000

About The Position

As a Senior Data Engineer, you will be responsible for designing, building, and maintaining robust data pipelines. Your key tasks will include creating and optimizing end-to-end data flows, handling ETL processes including extract, transform, and load, designing data models, ensuring data security and compliance, collaborating with cross-functional teams, and continuously improving performance and scalability. Your expertise will bridge the gap between raw data and actionable insights, enabling efficient data processing and analytics across the business. Here, you’ll work with and guide a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. You’ll use your experience in analytical exploration and data examination while you manage 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

7+ years of experience in designing and developing ETL processes and managing data pipelines
Experience using various AWS services, including AWS Glue, Amazon S3, and Amazon RDS
Knowledge of performance optimization techniques for ETL jobs, such as partitioning, bucketing, and caching
Ability to troubleshoot and improve query performance
Ability to develop and deploy ETL processes with limited visibility, utilizing comprehensive logging and robust error handling mechanisms to troubleshoot and resolve issues
Ability to proficiently write Python and PySpark code for ETL scripts and custom transformations
Ability to proficiently write SQL queries on a PostgreSQL database
Ability to design and implement data models, define schemas, and optimize data structures for efficient querying and analytics
Public Trust clearance
Bachelor’s degree in Computer science, Computer engineering, Information systems, or technology

Nice To Haves

Experience with cloud-native data services such as AWS Lambda or Google Cloud Functions and leveraging serverless architectures for data processing
Experience ensuring data quality, privacy, and security
Knowledge of data governance practices, data lineage, and compliance requirements such as GDPR and CCPA
Knowledge of tools like Apache Atlas, AWS Glue Data Catalog, or Collibra for managing metadata, data lineage, and cataloging data assets

Responsibilities

Designing, building, and maintaining robust data pipelines
Creating and optimizing end-to-end data flows
Handling ETL processes including extract, transform, and load
Designing data models
Ensuring data security and compliance
Collaborating with cross-functional teams
Continuously improving performance and scalability
Managing the assessment, design, building, and maintenance of scalable platforms