Graduate Data Engineering Intern, Data Science
AmplifAI Health
Data Science
Mountain View, CA, USA
Posted on Nov 23, 2024
LinkedIn was built to help professionals achieve more in their careers, and everyday millions of people use our products to make connections, discover opportunities, and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume – we transform lives through innovative products and technology.
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 2025 or later.
At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together. Our internship roles will be based in Mountain View, CA; or other US office locations.
Our internships are 12 weeks in length and will have the option of two intern sessions:
• May 27th, 2025 - August 15th, 2025
• June 16th, 2025 - September 5th, 2025
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.
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.
Equal Opportunity Statement
LinkedIn is committed to diversity in its workforce and is 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 an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: https://microsoft.sharepoint.com/:b:/t/LinkedInGCI/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1C_QxVTbg?e=5hfhpE. Please reference https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf for more information.
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.
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
This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice
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 2025 or later.
At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together. Our internship roles will be based in Mountain View, CA; or other US office locations.
Our internships are 12 weeks in length and will have the option of two intern sessions:
• May 27th, 2025 - August 15th, 2025
• June 16th, 2025 - September 5th, 2025
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.
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.
Equal Opportunity Statement
LinkedIn is committed to diversity in its workforce and is 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 an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: https://microsoft.sharepoint.com/:b:/t/LinkedInGCI/EeE8sk7CTIdFmEp9ONzFOTEBM62TPrWLMHs4J1C_QxVTbg?e=5hfhpE. Please reference https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf for more information.
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.
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
This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice
