Data Engineer

  • Fixed Salary + benefits
  • Hong Kong
  • Permanent, Full time
  • Capgemini Financial Services
  • 09 Dec 18

This is a great opportunity for a motivated and energetic technologist wanting to work across both company data and big data experiences. Start fresh and taking part in new chapter for an insurance company. He/she help define, roll out, and evolve a new enterprise service, in an entrepreneurial environment where you can achieve rapid professional growth and make meaningful contributions to the success of a digital insurer.


  • Understand how data flows within various systems to provide input on requirements for databases to ensure data is organized properly for reporting/analytics.
  • Develop business requirements to drive functional specifications for digital marketing, business intelligence, management dashboard, and reporting applications.
  • The acquisition, management, and documentation of data.
  • Work independently, or as part of a team, to design and develop Big Data solutions
  • Data wrangling of heterogeneous data and explore and discover new insights
  • Enhancing data collection procedures to include information that is relevant for building analytic systems
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Lead analysis, architecture, design, and development of data warehouse and business intelligence solutions
  • Work closely with cross function teams to ensure data integrity & completeness.


Technical Competent:

  • Gather and process raw data at scale (including writing scripts, web scraping, calling APIs, write SQL queries, etc)
  • Work closely with innovation team to integrate amazing innovations and algorithms into our production systems.
  • Process structured and unstructured data into a form suitable for analytical purpose.
  • Support business decisions with ad hoc analysis as needed.
  • Understanding and applications of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Neural Network, etc.
  • Experience with common data science toolkits, such as R, Weka, Kera, TensorFlow, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable.
  • Proficiency in using Python, Hadoop.
  • Experience with data visualization tools, such as D3.js, GGplot, etc.
  • Proficiency in using query languages such as SQL, Hive, Pig.
  • Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.