Company Description
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.
Job Description
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.
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 https://careers.linkedin.com/benefits.
Additional Information
Equal Opportunity Statement
We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.
If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation.
Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:
- Documents in alternate formats or read aloud to you
- Having interviews in an accessible location
- Being accompanied by a service dog
- Having a sign language interpreter present for the interview
A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.
LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
San Francisco Fair Chance Ordinance
Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.
Pay Transparency Policy Statement
As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
Global Data Privacy Notice for Job Candidates
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
