Big Data Infrastructure at LinkedIn

Aug 18 24 Comments

How is this team at LinkedIn? On call, code quality, promotions, impact, leadership, process, ease of deployments, etc.

Which team would you recommend for someone who mostly has experience building distributed web application backends? Definitely not a data science geek and I dont want to specialize in machine learning.

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TOP 24 Comments
  • LinkedIn / Eng chiknCurry
    Data Infra is a huge org. Which team? But agree with FB ☝️, data infra probably has the highest talent bar within LinkedIn.
    Aug 18 14
    • Quicken Loans / Eng the original persimmon
      APA isn’t in Data Infrastructure? I was under the impression that they had some overlap. Are there teams that are in both? My offer letter/background check said that I’m in data infrastructure, but my team seems to be in APA.
      Aug 18
    • LinkedIn lispring
      @QuickenLoans, Data infra is responsible for Online and Nearline Data. APA is responsible for offline data. What kind of data will you be working with? That should help clarify.

      By the way are you sure you’re not thinking of Systems and Infrastructure? Which is an interviewing track not a team.
      Aug 18
    • Quicken Loans / Eng the original persimmon
      My team works on a platform for real-time monitoring, built on top of Pinot. It also does some automated anomaly detection/analysis stuff (I can give the team name if it helps, but honestly you can probably already find it from google). So I guess it works with both, but leans towards offline.

      Also I did interview for systems and infrastructure, but my HireRight report said that my department code is "4020 - Data Infrastructure".
      Aug 18
    • LinkedIn lispring
      Then yea you work in Data Infra not APA
      Aug 18
    • Quicken Loans / Eng the original persimmon
      thanks! I feel kinda dumb for being confused for so long; it's dumb how a team that literally works on an analytics platform is in data infra
      Aug 18
  • LinkedIn data@scale
    I am in big data infrastructure group that comprises of Hadoop (HDFS, Spark, Tensorflow, Dali), UMP, Pinot, Presto and would be happy to talk about any specific questions you might have.
    Aug 18 2
    • MongoDB tlb_miss
      Any insight into the message / search team?
      Aug 21
    • LinkedIn / Mgmt
      QuickSQL

      LinkedIn Mgmt

      PRE
      Amazon, Microsoft, Lyft
      BIO
      Your definition of "real" is going to evolve as you get older.
      QuickSQLmore
      Message is Kafka/Samza which is not in APA.
      Search is Galene, which is not in APA.
      ElasticSearch has little power here.
      Aug 28
  • Facebook / Eng Leo Messi
    Superb team. Gem of LI
    Aug 18 0
  • LinkedIn aap0
    APA is very big and varies a lot. The data infra teams I would say are spark, ump, pinot, etc. The rest are your generic big data engineer.
    Aug 18 3
    • OP
      Which ones would you say have bigger scope? If i worked at the Pinot team for example, thats all i would be exposed to no?
      Aug 18
    • LinkedIn lispring
      By bigger scope do you mean how many teams would rely on you and what has the most oncall and support?
      Aug 18
    • OP
      Scope as in how many different systems I can contribute to / make an impact in
      Aug 18
  • LinkedIn / Mgmt
    C Harder

    LinkedIn Mgmt

    PRE
    Amazon, Microsoft
    BIO
    Your definition of "real" is going to evolve as you get older.
    C Hardermore
    Hadoop team has bigger scope including Spark, Gobblin, Dali
    Pinot is stable
    UMP is busy but in suboptimal shape
    ...
    Aug 18 0

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