Senior Data Engineer - Data Science

LinkedIn•Mountain View, CA

18d•Hybrid

About The Position

LinkedIn is the worlds 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. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. LinkedIn's 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 1 billion 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. 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.

Requirements

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)

Nice To Haves

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

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 LinkedIn's vision and mission.

Benefits

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 $125,000 to $206,000. 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 We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer.
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.
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.
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.