Data Engineering Research Assistant - Python & ETL Pipelines

Usmd; College Park (MD); Híbrido; USD 60.000 - 80.000; Jornada completa

Descripción de la vacante

The University of Maryland ARLIS invites applications for a Data Engineering Research Assistant. You will work with project teams to build and run Python-based data pipelines, prepare and validate data in databases, and implement search and retrieval components under senior staff guidance.

Ideal candidates have a Bachelor’s degree in a related field and hands-on Python experience, plus familiarity with ETL processes, databases, Linux CLI, Git workflows, PyTest, and Docker.

Formación

• Bachelor's degree in a relevant field.
• Professional or substantial project-based experience programming in Python.
• Experience designing data pipelines or ETL/ELT jobs that read from sources, transform data, and load into a database.
• Hands-on experience with at least one database (document or relational) including schema design, writing queries, and validating loaded data.

Responsabilidades

• Build and run Python-based data pipelines.
• Prepare, load, and validate data in databases.
• Help implement search and retrieval components under guidance of senior staff.
• Collaborate with project teams to ensure data quality and accessibility.

Conocimientos

Python programming

Data pipelines design

ETL/ELT development

Testing with Pytest

Educación

Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, or related field

Herramientas

Docker

Git

Linux command line

Descripción del empleo

The University of Maryland ARLIS invites applications for a Data Engineering Research Assistant. You will work with project teams to build and run Python-based data pipelines, prepare and validate data in databases, and implement search and retrieval components under senior staff guidance.

Ideal candidates have a Bachelor’s degree in a related field and hands-on Python experience, plus familiarity with ETL processes, databases, Linux CLI, Git workflows, PyTest, and Docker.