Remote Data Engineer - Cloud Pipelines & ML Ops

Booz Allen Hamilton; Town of Aurora (NY); On-site; USD 62,000 - 141,000; Full time

Job summary

Booz Allen Hamilton is looking for a Data Engineer in the Town of Aurora, NY area to design and implement data pipelines and platforms that organize and deliver both structured and unstructured data for mission-driven projects.

You will work with a multi-disciplinary team of data engineers, developers, and data consumers in a fast-paced, agile environment, applying modern ETL, data modeling, and MLOps practices.

Qualifications

• 3+ years of experience with data pipelines, including data acquisition, data prep, and database architecture.
• 3+ years of experience in ETL development using Java, Python, SQL, or Scala.
• 2+ years of experience with PostgreSQL or Kafka.
• Experience with AWS services.
• Experience with designing and implementing, containerizing, and deploying end-to-end automated data and ML pipelines, within a Cloud environment.
• Knowledge of the ML lifecycle and concepts to develop an MLOps ecosystem.
• Top Secret clearance.
• Bachelor’s degree.

Responsibilities

• Implement data engineering activities on mission-driven projects and deploy data pipelines and platforms to organize data from disparate sources.
• Collaborate with data engineers, developers, and data consumers in an agile environment.
• Develop and deploy end-to-end automated data and ML pipelines within cloud environments.
• Support data organization, accessibility, and meaningful data delivery for stakeholders.

Skills

Data pipelines

ETL development

Java

Python

SQL

Scala

PostgreSQL

Kafka

AWS services

Cloud-based pipelines

ML pipelines / MLOps

Top Secret clearance

Bachelor's degree

Education

Bachelor’s degree

Tools

Kafka

PostgreSQL

Job description

Booz Allen Hamilton is looking for a Data Engineer in the Town of Aurora, NY area to design and implement data pipelines and platforms that organize and deliver both structured and unstructured data for mission-driven projects.

You will work with a multi-disciplinary team of data engineers, developers, and data consumers in a fast-paced, agile environment, applying modern ETL, data modeling, and MLOps practices.