Senior Data Engineer - Data Science

Sunnyvale, CA, United States

LinkedIn is the worlds largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters.

This role will be based in Sunnyvale or San Francisco.

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 work from home and commute to a LinkedIn office, depending on whats best for you and when it is important for your team to be together.

LinkedIns Data Science team leverages big data to empower business decisions and deliver data-driven insights, metrics, and tools in order to drive member engagement, business growth, and monetization efforts. With over 800 million members around the world, a focus on great user experience, and a mix of B2B and B2C programs, LinkedIn offers countless ways for an ambitious data engineer to have an impact and transform your career.

We are now looking for a talented and driven individual to accelerate our efforts and be a major part of our data-centric culture. This person will work closely with various cross-functional teams such as product, marketing, sales, engineering, and operations to develop infrastructure and deliver tools or data structures that enable data-driven decision-making. Successful candidates will exhibit technical acumen and business savviness with a passion for making an impact by enabling both producers and consumers of data insight to work smarter.

Responsibilities:

? Work with a team of high-performing data science 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 manage complex data systems for a product or a group of products.

? Perform all of the necessary data transformations to serve products that empower data-driven decision making.

? Build and manage data pipelines, design and architect databases.

? 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.

? Ensure best practices and standards in our data ecosystem are shared across teams.

? Understand the analytical objectives to make logical recommendations and drive informed actions.

? Engage with internal platform teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms.

? Be a self-starter, Initiate and drive projects to completion with minimal guidance.

? Contribute to engineering innovations that fuel LinkedIns vision and mission.

Basic Qualifications:

? Bachelor's Degree in a quantitative discipline: Computer science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics, etc.

? 3+ years of relevant industry or relevant academia experience working with large amounts of data

? Experience with SQL/Relational databases

? Background in at least one programming languages (e.g., R, Python, Java, Scala, PHP, JavaScript)

Preferred Qualifications:

? BS and 5+ years of relevant work experience, MS and 3+ years of relevant work experience, or Ph.D. and 1+ years of relevant work/academia experience working with large amounts of data

? MS or PhD in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.

? 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 with manipulating massive-scale structured and unstructured data.

? Experience with using distributed data systems such as Spark and related technologies (Presto/Trino, Hive, etc.).

? Experience with either data workflows/modeling, front-end engineering, or back-end engineering.

? Deep understanding of technical and functional designs for relational and MPP Databases

? Experience in data visualization and dashboard design including tools such as Tableau, R visualization packages, streamlit, D3, and other libraries, etc.

? Knowledge of Unix and Unix-like systems, version control systems such as Git.

Suggested Skills:

? Distributed Systems

? ETL

? Data Modeling

You will Benefit from our Culture:

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $117,000.00 to $192,000.00 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.

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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 [email protected] 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.

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