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Data Engineer (Intern)

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Job updated 10 meses ago

Descripción del trabajo

KKLab is seeking a talented data engineer intern working with our engineering team to  build systems that collect and convert raw data into usable information for our AI systems, including recommendation engines, data analytics platforms, as well as systems that manage the data workflows among different components.  

KKLab has a recommendation platform in the market, KKRaaS. KKBOX is using our platform to provide personalized music recommendations for its users. Our candidate will be working on enhancing the data pipelines, which feed data into the recommendation platform, to improve the operational efficiency, reliability and maintainability of KKBOX recommendation.

We are looking for a candidate who is self-motivated with strong coding skills and passionate about engineering excellence. We build our system by combining our in-house solutions with AWS cloud services and open source software. The candidate should be also familiar with the open source data engineering ecosystem. 

Responsibility

  • Design, implement and optimize automated workflows to minimize human effort required in running machine learning processes, ETL processes, etc.
  • Design and implement internal developer toolchains to facilitate the progress of data pipelines.

Requisitos

Minimum Qualifications:

  • Working experience in Python, Java, Scala, shell script.
  • Working experience with tools that can help cloud service development, e.g. Kubernetes, Ansible, Terraform, Docker, etc.
  • Familiarity with relational databases and NoSQL DB.
  • Familiarity with big data technologies, such as Hive, Hadoop, Presto, Spark.

Proceso de entrevista

Team, bar raiser / 60~90m / Google Meet, On-line Coding

Please submit your application via KKLab Career Website (https://kklab.freshteam.com/jobs), as we will prioritize applicants resume on Career Website.

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Sobre nosotros

KKLab is a venture studio, formed by 30 data scientists & venture technologists. We seek joint-ventures with influential experts to demystify machine learning necessary to building valuable business. We work hybrid - 4 days WFH and 1 day IRL. If you are interested in building future businesses rooted in purpose, we want to get to know you.


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