Data Engineer- Data Science Intern, Master's - Summer 2026

LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works.

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, you’ll 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, HDFS, Hive, 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.