Full Time
Junior (less than 3 years)
English, Cantonese, Mandarin (Putonghua)

Job Description

Senior Engineer/Engineer, Data Analytics

Job Responsibilities

  • Develop compelling PoC’s and solutions using emerging technologies for real-time and big data ingestion and processing.
  • Responsible for the design and implementation of BDA solutions using a modern Big Data toolkit (Hadoop, Spark, Storm, NoSQL etc.).
  • Closely collaborate with other developers and architects in developing client solutions.


  • BS, MS or PhD holder in Computer Science, Engineering, Statistics, Mathematics or related field. Fresh graduates are welcome.
  • Have passion and experience in programming in one of more following languages: Java/scala/python/R.
  • Strong data modeling and SQL experience.
  • Development experience in machine learning, data mining, and real-time processing is a big plus.
  • Hands-on experience of working in a big data (hadoop,spark,mapreduce) environment is highly preferred.
  • Strong analytical and communication skills.
  • Excellent command of English, fluency in Cantonese and Mandarin is a plus.
  • Self- motivated and fast learner.


Appointment will be on renewable contract terms with a competitive salary and performance-linked variable pay. Fringe benefits include paid leave, medical and dental benefits, insurance coverage and contribution to MPF. The incumbent will normally work under a five-day week schedule.

Interested candidates should send application (quoting Ref. No.) with detailed resume and, current and expected salary to the HR Department by email (preferable) or post no later than 30 October 2016.

Email: [email protected]
Post: 5/F, Photonics Centre, 2 Science Park East Avenue,
Hong Kong Science Park, Shatin, Hong Kong.

Only short-listed candidates will be notified. Personal data provided by applicants will be used for recruitment purposes only.

Technical Skills

  • Apache Hadoop
  • Big Data
  • Data Mining
  • Data Modeling
  • Java
  • Machine Learning
  • Mathematics
  • Python
  • R
  • SQL
  • Statistics