Data Engineer - Data Science

Company Description

Linked In 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.

Join us to transform the way the world works.

Linked In'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, Linked In 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 Linked In, 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 Linked In office on select days, as determined by the business needs of the team.

• 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 Linked In's vision and mission.

• 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)

• 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.

• 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 Linked In is committed to fair and…