Senior Data Engineer - Data Science

$121,000 - $198,000/Yr

LinkedIn - Sunnyvale, CA

Full-time - Mid Level

Remote - Sunnyvale, CA

About the position

The Senior Data Engineer role at LinkedIn focuses on leveraging big data to empower business decisions and deliver data-driven insights. This position involves collaborating with cross-functional teams to develop infrastructure and tools that facilitate data-driven decision-making, ultimately driving member engagement and business growth. The role offers a hybrid work option, allowing flexibility in work location while contributing to a data-centric culture.

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 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 and 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.

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 language (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 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.

Benefits

• Generous health and wellness programs
• Time away for employees of all levels
• Annual performance bonus
• Stock options
• Comprehensive benefits package