Senior Data Engineer - Data Science

LinkedIn is seeking a Senior Data Engineer for their Data Science team. This role will leverage big data to empower business decisions and deliver data-driven insights, metrics, and tools to drive member engagement, business growth, and monetization efforts. The ideal candidate will work closely with cross-functional teams to develop infrastructure and deliver tools or data structures that enable data-driven decision-making.

Key Responsibilities:

• Work with high-performing data science professionals and cross-functional teams to identify business opportunities and build scalable data solutions
• Build data expertise and manage complex data systems for products
• Perform 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 technical and non-technical partners
• Design, implement, integrate, and document performant systems for data flows and analysis at massive scale
• Ensure best practices and standards in the data ecosystem are shared across teams
• Understand analytical objectives to make logical recommendations and drive informed actions
• Engage with internal platform teams to prototype and validate tools for deriving insights from large datasets
• Be a self-starter, initiating and driving projects to completion with minimal guidance
• Contribute to engineering innovations that fuel LinkedIn's vision and mission

Required 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 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)

Preferred Qualifications:

• MS or PhD in a quantitative discipline
• Experience in developing data pipelines using Spark and Hive
• Experience with data modeling, ETL concepts, and efficient data governance
• Experience with distributed data systems (Spark, Presto/Trino, Hive, etc.)
• Deep understanding of technical and functional designs for relational and MPP Databases
• Experience in data visualization and dashboard design
• Knowledge of Unix and version control systems like Git

LinkedIn offers a hybrid work option, generous health and wellness programs, and fair and equitable compensation practices. The company is committed to diversity, equal opportunity, and creating an inclusive workplace.