Remote Data Engineer: Build Scalable Pipelines for Impact

Booz Allen Hamilton; Virginia; Hybrid; USD 62,000 - 141,000; Full time

Benefits offered by this job

Health insurance

Retirement benefits

Paid time off

Tuition assistance

Job summary

Booz Allen Hamilton is seeking a Data Engineer to design and deploy data pipelines that transform structured and unstructured data to support mission-focused projects across fraud detection, cancer research, and national intelligence. You’ll work with a multidisciplinary team in a fast-paced, agile environment to organize data from disparate sources and deliver scalable platforms.

The role requires 2+ years of data engineering, ETL, Python, SQL, and cloud/automation experience.

Qualifications

• 2+ years of experience with data engineering, pipeline development, data science, data analytics, machine learning, or software engineering.
• Experience with ETL operations.
• Experience with source control and collaboration software, including Git or Atlassian tools.
• Experience writing software in Python.
• Knowledge of relational and non-relational database technologies, including SQL or GraphQL.
• Knowledge of automation and scripting on Linux or Windows.
• Secret clearance
• Bachelor's degree

Responsibilities

• Develop and deploy the pipelines and platforms that organize disparate data.
• Collaborate with analysts, data engineers, developers, and data consumers in a fast-paced, agile environment.
• Support assessment, design, development, and maintenance of scalable data platforms for clients.

Skills

Python

ETL

SQL

Git

AWS

Data pipelines

Education

Bachelor's degree

Master's degree

Tools

Databricks

Spark

Terraform

Job description

Booz Allen Hamilton is seeking a Data Engineer to design and deploy data pipelines that transform structured and unstructured data to support mission-focused projects across fraud detection, cancer research, and national intelligence. You’ll work with a multidisciplinary team in a fast-paced, agile environment to organize data from disparate sources and deliver scalable platforms.

The role requires 2+ years of data engineering, ETL, Python, SQL, and cloud/automation experience.