Data Engineer- Data Science Intern, Master's Summer 2026 (Mountain View, CA)

This internship role will be based out of Headquarters in Mountain View California. 
 
At LinkedIn our approach to flexible work is centered on trust and optimized for culture connection clarity and the evolving needs of our business. The work location of this role is hybrid meaning it will be performed both from home and from a LinkedIn office on select days as determined by the business needs of the team. 

 
As a data engineer intern youll be transforming our data ecosystems. You will conduct a variety of applied research on the rich data that flows through our systems while effectively leveraging our data to create a single source of truth data. Successful candidates will exhibit technical acumen and business savvy with a passion for making an impact through creative storytelling and timely actions. 
 
You will be working on our big data technology stack consisting of a variety of distributed platforms; we utilize both open-source and proprietary frameworks for large scale data processing including Hadoop HDFSHive and Spark. We also use Kafka for ingestion Azkaban for workflow management in addition to other applications. 
 
Candidates must be currently enrolled in a graduate degree program with an expected graduation date of December 2026 or later. 
 
Our internships are 12 weeks in length and will have the option of two intern sessions: 
May 26th 2026 - August 14th 2026 
June 15th 2026 - September 4th 2026 

Responsibilities: 
 
Work with a team of high-performing data engineering professionals and cross-functional teams to identify business opportunities and build scalable data solutions. 
Build data expertise act like an owner for the company and help manage complex data systems for a product or group of products. 
Perform all of the necessary data transformations to serve products that empower data-driven decision making. 
 Establish efficient design and programming patterns for engineers as well as for non-technical partners. 
Design implement integrate and document performant systems or components for data flows or applications that power analysis at a massive scale. 
Understand the analytical objectives to make logical recommendations and drive informed actions. 
Engage with internal data platform teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms.

Qualifications :

Basic Qualifications: 
Currently pursuing a Graduate Degree in a quantitative discipline: computer science statistics applied mathematics operations research management of information systems engineering economics or equivalent and returning to the program after the completion of the internship. 
Experience in at least one programming language (eg. Python R Hive Java Ruby Scala/Spark or Perl etc.). 
Experience with SQL or other relational databases. 
 
Preferred Qualifications: 
Experience in Hadoop or other MapReduce paradigms and associated languages such as Pig and Hive. 
Proven experience in developing data pipelines using Spark and Hive. 
Experience with data modeling ETL (Extraction Transformation & Load) concepts and patterns for efficient data governance. 
Experience working with databases that power APIs for front-end applications. 
Understanding data visualization tools (eg. Tableau BI dashboarding R visualization packages etc.). 
Experience building front-end visualizations using JavaScript frameworks (eg. jQuery Marionette D3 or Highcharts). 
Experience in applied statistics and statistical modeling in at least one statistical software package (eg. Advance R package SAS SPSS). 
Ability to communicate findings clearly to both technical and non-technical audiences. 
 
Suggested Skills: 
Object-oriented Programming (OOP) 
SQL or other relational databases 
Distributed Systems 
 
LinkedIn is committed to fair and equitable compensation practices. 
 
The pay range for this role is $49 - $60 per hour. Actual compensation packages are based on several factors that are unique to each candidate including but not limited to skill set depth of experience certifications and specific work location. This may be different in other locations due to differences in the cost of labor. 
 
The total compensation package for this position may also include annual performance bonus stock benefits and/or other applicable incentive compensation plans. For more information visit Information :

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No

Employment Type :

Full-time