Data Engineer

Naval Nuclear Laboratory•West Mifflin, PA

12d

About The Position

As an Advanced Data Engineer within the Data Engineering Unit, you will be an integral part of our team, focusing on designing, building, and maintaining scalable data pipelines and architectures. You will work to ensure the smooth and efficient flow of data across our systems, supporting our organization's analytical and operational needs. Your role will involve collaborating with data scientists, analysts, and other stakeholders to understand data requirements and implement robust solutions. Your technical skills and proactive approach will be critical in optimizing data processes and ensuring data quality and reliability. Ready to make an impact? Apply now and help us build scalable data solutions that power critical analytics across our organization!

Requirements

Bachelors degree from an accredited college or university in a related engineering or science field and a minimum of 4 years of relevant experience; or Masters degree from an accredited college or university in a related engineering or science field and a minimum of 2 years of relevant experience; or Doctorate degree from an accredited college or university in a related engineering or science field; or Currently an Advanced Reactor Training Engineer, Refueling Engineer, or Field (RPCO) Engineer at the Company.

Nice To Haves

Strong problem solving and analytical skills.
Solid experience in developing and managing data pipelines, ETL processes, and data architecture.
Proficiency in programming languages such as SQL and Python, and experience with big data technologies like Apache Spark or Hadoop.
Experience with database management systems, both relational and non-relational.
Understanding of data modeling and warehousing principles.
Ability to collaborate effectively with data scientists, analysts, and other technical and non-technical stakeholders.
Good communication and interpersonal skills, capable of explaining complex data concepts to diverse audiences.
A proactive approach to learning new technologies and improving existing processes.

Responsibilities

Designing, building, and maintaining scalable data pipelines and architectures.
Ensuring the smooth and efficient flow of data across systems.
Supporting the organization's analytical and operational needs.
Collaborating with data scientists, analysts, and other stakeholders to understand data requirements and implement robust solutions.
Optimizing data processes and ensuring data quality and reliability.