Data Engineering Internship

Data Engineering Internship

Job Overview

Location
Piscataway, New Jersey
Job Type
Internship
Job ID
92685
Date Posted
1 year ago
Recruiter
Carla Tomasi
Job Views
969

Job Description

Colgate-Palmolive invites you to apply for the Spring 2022 Data Engineering Internship for the Global Information Technology (GIT) organization. The purpose of this internship is to work on different aspects of data warehousing. This includes but is not restricted to data engineering pipelines in a cloud data warehouse, practices and technology. While doing so, the candidate is also expected to learn data management practices like data quality, data governance processes along with developing a deeper understanding of Analytics in digital domain and how it is  by Colgate business to drive decisions. 

 Responsibilities will include: 

  • Create and maintain data pipeline architecture,

  • Assemble large, complex data sets that meet functional / non-functional business requirements.

  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery

  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources

  • Assist with data-related technical issues and support their data infrastructure needs.

  • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an

  • innovative industry leader.

  • Work with data and analytics experts to strive for greater functionality in our data systems

 Qualifications:

  • Authorized to work in the U.S. without requiring sponsorship now or in the future

  • Must be currently enrolled in a Bachelor’s or Master’s degree program (Master’s degree preferred)

  • Majoring in Computer Science, Data Science, Statistics or a similar field with a focus on predictive analytics 

  • A minimum GPA of 2.8

  • Ability to work in a high-pressure, fast-paced environment

  • Availability to work a minimum of 15-20 hours per week

  • Preferred knowledge and experience with Python, Github, Docker, Kubernetes, SQL




Job ID: 92685

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