Data Science & Engineering Team Lead (Hadoop, Apache Airflow, Spark, ETL, Python, AWS)

  • Competitive Base + Bonus
  • Hong Kong
  • Permanent, Full time
  • BAH Partners
  • 21 May 19

My client is one of the fastest growing international tech firms in Hong Kong right now. They are extremely well established after a decade and its product is globally #1 in its niche. They have been experiencing double digit growth in the past 5 years. They are cash rich, privately funded, with state-of-the-art offices in the heart of Hong Kong.


  • In short, this is a people management role leading a team of Data Scientists & Data Engineers.
  • We are looking for someone who likes to remain hands-on in building data pipelines, building machine learning models, creating data-driven business insights, all the while mentoring and developing people.
  • You would be the Subject Matter Expert on all things Data - providing technical solutions on ETL tools, data warehousing, visualization, and creating data-driven insights to answer mission critical business questions 
  • This is a business aligned role where your insights will directly impact the firm's product decisions across their iOS, Mac, Android, Windows, Linux, Web platforms.
  • Work with cutting edge data technologies: Apache Airflow, Spark, Hadoop, AWS Services, Google Services, Python, Pandas, Jupyter notebooks, Tableau, Grafana, Postgres, InfluxDB, Redshift, BigQuery

Company & Software Development Culture:

  • Extremely international (English-speaking), flat structure, meritocratic environment, excellent opportunities for advancement. 
  • Agile Scrum methodology, TDD, CI/CD, DevOps heavy, microservices architecture 


  • Proven experience in directly managing people is a must 
  • Expertise in building data pipelines, ETL tools & processes, and using data science to generate insights for the business 
  • Proficiency in at least one programming language (preferably Python) 
  • Excellent communication and stakeholder engagement skills in English
  • Educational background in a quantitative subject or Computer Science