Data Engineer for Large Scale Data Solutions
2 days ago
As a pioneer in professional networking, LinkedIn empowers members to achieve their career goals. Our mission is to create economic opportunities for the global workforce by providing innovative solutions that foster connections and drive growth. We strive to be a workplace where everyone feels valued and has the skills needed to succeed.
The Data Science team at LinkedIn utilizes big data to inform business decisions and deliver insights, metrics, and tools that enhance member engagement, business expansion, and revenue generation. With over 800 million users worldwide, we offer diverse opportunities for ambitious data engineers to make an impact and advance their careers.
- We are seeking a talented individual to accelerate our data-centric efforts and contribute to our collaborative culture.
The successful candidate will work closely with 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. Key responsibilities include:
Responsibilities:
- Collaborate with high-performing data science professionals and cross-functional teams to identify business opportunities and build scalable data solutions.
- Develop expertise in data management, act as a company owner, and manage complex data systems for products or groups of products.
- Perform necessary data transformations to serve products empowering data-driven decision making.
- Design, implement, integrate, and document performant systems or components for data flows or applications powering analysis at massive scales.
- Evaluate best practices and standards in the data ecosystem to share across teams.
- Understand analytical objectives to provide logical recommendations and drive informed actions.
- Engage with internal platform teams to prototype and validate tools developed in-house to derive insight from large datasets or automate algorithms.
- Be a self-starter, initiate, and drive projects to completion with minimal guidance.
- Contribute to engineering innovations fueling LinkedIn's vision and mission.
- Bachelor's degree in a quantitative discipline: Computer science, Statistics, Operations Research, Informatics, Engineering, Applied Mathematics, Economics, etc.
- 5+ 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)
- 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 developing data pipelines using Spark and Hive
- Experience with data modeling, ETL concepts, and patterns for efficient data governance
- Experience manipulating massive-scale structured and unstructured data
- Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.)
- Experience with 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, D3, and other JavaScript libraries
- Knowledge of Unix and Unix-like systems, git, and review board
$170,000 - $220,000 per annum, depending on location and qualifications
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