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Data Engineer | Linkedin Careers | Job Alert | Latest Job Update 2022

Data Engineer | Linkedin Careers | Job Alert | Latest Job Update 2022

Data Engineer | Linkedin Careers | Job Alert | Latest Job Update 2022

About Company

LinkedIn is the wоrld’s lаrgest рrоfessiоnаl netwоrk, built tо helр members оf аll bасkgrоunds аnd exрerienсes асhieve mоre in their саreers. Оur visiоn is tо сreаte eсоnоmiс орроrtunity fоr every member оf the glоbаl wоrkfоrсe. Every dаy оur members use оur рrоduсts tо mаke соnneсtiоns, disсоver орроrtunities, build skills аnd gаin insights. We believe аmаzing things hаррen when we wоrk tоgether in аn envirоnment where everyоne feels а true sense оf belоnging, аnd thаt whаt mаtters mоst in а саndidаte is hаving the skills needed tо suссeed. It insрires us tо invest in оur tаlent аnd suрроrt саreer grоwth. Jоin us tо сhаllenge yоurself with wоrk thаt mаtters.

Data Engineer Job Description

In order to drive member engagement, business growth, and monetization efforts, LinkedIn’s Data Science team leverages big data to empower business decisions and deliver data-driven insights, metrics, and tools. A career at LinkedIn offers countless opportunities for an ambitious data scientist to make an impact, with over 600 million members worldwide, a focus on great user experience, and a mix of B2B and B2C programmes.

We are now looking for a talented and motivated individual to help us accelerate our efforts and contribute to our data-centric culture. This individual will collaborate closely with various cross-functional teams, including product, marketing, sales, engineering, and operations, to develop and deliver tools or data structures that provide actionable recommendations to business partners. Successful candidates will demonstrate technical and business acumen, as well as a desire to make a difference by enabling both producers and consumers of data insight to work smarter.

Roles and Responsibilities

  • Work with a team of high-performing analytics, data science professionals, and cross-functional
  • teams to identify business opportunities, optimize product performance or go to market strategy.
  • Build data expertise, act like an owner for the company and manage complex data systems for a
  • product or a group of products.
  • Performing all of the necessary data transformations to serve products that empower data-driven
  • decision making.
  • Establishing efficient design and programming patterns for engineers as well as for non-technical
  • partners.
  • • Designing, integrating and documenting technical components for data flows or applications that
  • perform analysis at a massive scale.
  • • Ensuring 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.
  • • Initiate and drive projects to completion with minimal guidance.
  • • Contribute to engineering innovations that fuel LinkedIn’s vision and mission


  • Bаsiс Quаlifiсаtiоns | Linkedin Recruitment 2021
    • Bachelor in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
    • 3+ years relevant industry or relevant academia experience working with large amounts of data
    • 2 + years’ experience with SQL/Relational databases
    • 2 + years’ experience with manipulating massive-scale structured and unstructured data.
    • Experience with distributed data systems such as Hadoop and related technologies (Spark, Presto, Pig, Hive, etc.).
    • Background in at least one programming language (e.g., R, Python, Java, Scala, PHP, JavaScript)
    • Experience with data modelling, ETL (Extraction, Transformation & Load) concepts, and patterns for efficient data governance.
    • Working knowledge of Unix and Unix-like systems, git and review board 
  • Рreferred Quаlifiсаtiоns
    • Masters or Ph.D. degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
    • Bachelors with 3+ years or Masters with 2+ years of industry experience
    • Experience in developing data pipelines using Spark and Hive.
    • Experience with either data workflows/modeling, front-end engineering, or back-end engineering.
    • Experience in either the front-end or back-end development of data-powered applications.
    • Deep understanding of technical and functional designs for relational and MPP Databases, Reporting and Data Mining systems.
    • Strong communication skills, with the ability to synthesize, simplify and explain complex problems to different audiences.
    • Experience working with databases that power APIs for front-end applications.
    • Experience working in the product, sales, or marketing analytics domains.
    • Experience in data visualization and dashboard design including tools such as Tableau, R visualization packages, D3, and other Javascript libraries, etc.

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