You will be working with varied stakeholders in an exciting, dynamic and fast-paced environment. You’ll help us to build the data models to support anlytics to retain our customers and be part of a rapidly expanding analytics team. 

The job holder will use his expertise to develop and maintain large scale data pipelines, streamline the data flow process but not limited to support the development of ML models, and provide high quality insights to our loyalty program partners’ trading and marketing teams and/or FMCG suppliers.

Is this your next challenge in data engineerring?

The challenge is to:

• To develop and maintain the large and scalable data pipeline using cloud services and ensure its performance
• To support the team in data sourcing, extraction, cleansing, transformation, and validation of complex data sets that meet non-functional and functional business requirements
• To collaborate with analytics and business teams to improve data science models, increase data accessibility for business intelligence tools, and foster data-driven decision making across the organization
• To solve data problems and able to provide insights for both technical and non-technical audiences
• To identify, design and implement process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
• To design data models, data integration and governance framework
• To cross check, debug, and solve issues to ensure your team’s deliverable's accuracy and clarity, even when confronted by subtle data complications

Do you have experience in data modeling?

• A Bachelor’s degree in Computer Science / Statistics / Mathematics / Operations Research / Data Science or other related quantitative fields
• 3+ years of experience as a data engineer or other quantitative data role
• Hands-on experience with Python, Google Analytics, SQL databases
• Build processes supporting ETL, data structures, metadata, dependency, and workload management in a large and complex data environment
• Experience in big data product development, including data warehouse, query platform, streaming, recommendation, user profiling, etc.
• Experience in building web scrapers to collect external data
• Experience with BI & data visualization tools (Tableau preferred)
• Experience with Google Cloud Platform/ Microsoft Azure or other cloud services
• Experience with building APIs and applications with flask, FastAPI, etc.
• Project and vendor management experience
• Motivated to proactively seek out opportunities to add value from data and willingness to learn new tools, skills and coding languages
• Track record of good people skills and team orientation; quality-oriented, highly committed and professional
• Excellent communication skills in English, Cantonese and Mandarin

Preferred Requirements

• A Master’s degree or PhD in Computer Science / Statistics / Mathematics / Operations Research / Data Science or other related quantitative fields
• Experience in common data science languages/toolkits, such as Python, SQL, R, Scala, Apache Spark, Keras, or other statistical / machine learning software
• Experience with databricks and Spark (pyspark or Scala)
• Knowledge of HTML/CSS/JavaScript, d3.js and web application frameworks (Flask, Django, Play!, R Shiny, etc.)
• Experience with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, DevOps and Project Management Tool
• Experience with Docker and Kubernetes
• Experience with NoSQL (Neo4j, MongoDB, ElasticSearch, etc.)
• Familiar with Graph Theory and Neo4j
• Candidates with data scientist experience are welcome