Data Engineer

Booz Allen Hamilton•Arlington, VA

1d•$62,000 - $141,000•Hybrid

About The Position

As a data engineer at Booz Allen, you’ll use your skills and experience to help build advanced technology solutions and implement data engineering activities on some of the most mission-driven projects in the industry. You’ll develop and deploy the pipelines and platforms that organize and make disparate data meaningful. Here, you’ll work with a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. You’ll sharpen your skills in analytical exploration and data examination while you support the assessment, design, developing, and maintenance of scalable platforms for your clients. Work with us to use data for good.

Requirements

5+ years of experience designing, building, and maintaining data pipelines in production environments
3+ years of experience developing with distributed systems such as Spark or PySpark
3+ years of experience with data lakehouse or warehouse platforms, schema design, and query optimization
3+ years of experience processing data using streaming, including Kafka or Kinesis, and batch methods
Experience in Python and SQL
Experience implementing best practices for data quality, testing, and observability
Knowledge of structured or unstructured data formats such as Parquet, Avro, JSON, or Delta
Knowledge of data, information, and message exchange structures and standards
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor's degree

Nice To Haves

3+ years of experience in data analytics
Experience designing data flows that leverage a medallion architecture
Experience with containerization and orchestration such as Docker, Kubernetes, or EKS
Experience with Kafka and Nifi
Experience using AWS
Experience developing with Databricks
Experience in Scala or Java
Knowledge of microservices and integrating with data services
Knowledge of database schema design
Master's degree

Responsibilities

Designing, building, and maintaining data pipelines in production environments
Developing with distributed systems such as Spark or PySpark
Working with data lakehouse or warehouse platforms, schema design, and query optimization
Processing data using streaming, including Kafka or Kinesis, and batch methods
Implementing best practices for data quality, testing, and observability
Designing data flows that leverage a medallion architecture
Developing with Databricks
Integrating with data services