Data/AI Engineer, Data Manipulation PySpark Panda

Department: HOT HK
Salary: $33K HKD per month + x 12 months

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RECRUITER SUMMARY

HOT_HK Data Scientist, Data/AI Engineer, Data Manipulation PySpark Panda, $33K HKD per month

22/02/2024

Candidate Background

Nationality:
Hong Konger
Residence:
Hong Kong
Education:
Bachelor Degree Of Engineering ­ Computer Science XXXX, Associate Of Engineering ­ Computer Science XXXX
Languages:
English – Fluent, Mandarin – Fluent, Cantonese – Native
Experience:
3+ years of experience in the industry Current & Previous Employers and jobs include: Data Engineer at XXXX, Research Assistant, Software Development at XXXX, AI Engineer at XXXX, Student Research Assistant at XXXX
Motives:
Is passively looking for a job right now and is just looking out for opportunities in the market. Open for Data Engineer roles.
Current Salary:
$25K HKD per month + Bonus x 13 months
Expected Salary:
$33K HKD per month + x 12 months
Notice Period:
1 Month
Interview Availability:
Requires a day notice

Interview Assessment Notes

  1. Could you introduce yourself and tell us about you? Your current / recent jobs and employers? Previous companies and jobs?
    He is currently a Data Engineer for XXXX Limited where he mainly do data manipulation, extracting data from data warehouse and automate them on some tools and cloud platform. His skillset is mostly working on ETL pipelines, Python, PySpark, and SQL. Before this, he has several experiences as a Research Assistant for Software Development and was an AI Engineer for XXXX.
  2. What skill(s) / experience would you self-describe as strongest or specialist in?
    Strongest skill would be on data engineering side; strong as well with problem solving and good with data manipulation using PySpark or Pandas.
  3. Do you have the lists of key criteria’s according to the clients’ requirements?
    Has 2-3+ years of experience in the data engineering industry. Strong with Python, has tried C++ during university, also familiar with JavaScript. For the databases, he is mostly using SQL and for the cloud platform, they are using HPE. Good with building automated data pipelines and mapping across databases.

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