Systems & Infrastructure Engineer Intern, PhD (Materialized View) 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. 

Are you interested in large-scale data processing We are building the next generation of LinkedIns data infrastructure spanning analytical compute data storage and lakehouse platforms that power insights analytics and intelligent products across the company. As LinkedIn continues to grow in membership usage and data volume you will help scale systems that process and query massive datasets reliably and efficiently.

In this role you will work with distributed data processing engines and algorithms developing a strong systems mindset around scalability performance and correctness. You will gain hands-on experience with query execution data partitioning caching and distributed storage and contribute to production systems built on and alongside cutting-edge open-source technologies.

Candidates must be currently enrolled in a PhD program with an expected graduation date 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 

The ideal intern will contribute to scaling LinkedIns data infrastructure to support continued growth in membership traffic and data volume. As usage of our products continues to expand this role will focus on building and supporting large-scale data systemssuch as Apache Spark Flink Trino Iceberg and Airflowthat power self-serve analytics reporting interactive querying and the data pipelines behind LinkedIns machine learning and AI-powered products.

As part of this work the intern will:

• Design and optimize distributed data processing and query execution workflows operating at LinkedIn scale.

• Develop data abstractions and optimizationssuch as materialized views and query rewritingto improve performance efficiency and data freshness for analytics and AI workloads.

• Contribute to the reliability and scalability of production data pipelines through monitoring correctness validation and performance tuning.

Qualifications :

Basic Qualifications:
Currently pursuing a PhD Degree in Computer Science or related technical field and
returning to the program after the completion of the internship.
Programming experience in one or more of the following languages: Java Scala Python.
Knowledge of core computer science concepts such as object-oriented design algorithm
design data structures problem-solving and complexity analysis

Preferred Qualifications:
Experience working in a fast-paced agile and iterative development environment with exposure to design reviews code reviews and incremental delivery of production systems.

Strong foundation in computer science fundamentals including data structures algorithms software design and object-oriented programming with an understanding of database management systems query processing and query planning and optimization.

Familiarity with analytical query engines and optimization techniques including materialized views query rewriting and cost-based optimization or a strong interest in learning these areas.

Exposure to open-source data and query processing technologies such as Apache Spark Trino Calcite and Iceberg and an interest in how these systems are built integrated and evolved.

Ability to reason about correctness performance and scalability in data-intensive systems and to clearly communicate technical ideas in both written and verbal form.

Suggested Skills: 

Distributed Data Processing 

Database Systems and Query Processing 

Query Optimization and Execution Engines 

Large-Scale Data Management (Lakehouse Systems) 

Performance and Scalability Engineering
 

As part of the application process for this role after an initial qualifications review candidates are required to successfully complete the HackerRank online code challenge. Instructions for completion of the code challenge will be sent to you if your application is selected to move forward in the process.

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $65-$75. 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