Job Description
47 days ago
Responsibilities
• Manage the enterprise analytics data platform and optimize the scalability and performance of the platform
• Act as a data architecture SME and provide advisory to data engineers and application teams for data architecture principles, standard and best practice
• Work closely with our data scientists to deliver world class data products and refactor code into reusable libraries, APIs or tools
• Use agile software development processes to iteratively make improvements to our back-end systems
• Model front end and back-end data sources to help draw a more comprehensive picture of user flows throughout our system and enable powerful data analysis
• Design, implement, test, deploy, and maintain stable, secure, and scalable data engineering solutions and pipelines in support of data and analytics projects, including integrating new sources of data into our enterprise analytics data platform, maintaining feature store, and moving data out to applications and affiliates
• Produce scalable, replicable code and engineering solutions that help automate repetitive data management tasks
• Collaborate with different stakeholders to Implement and ensure data governance model is in place on enterprise level
• Coaching junior staffs and take lead in new initiative
• Co-develop data analytics/technology roadmaps, and to correspondingly build and continue improve data architecture
Requirements
• Bachelor’s degree or above in Computer Science, Engineering or related fields
• Minimum 6 years of relevant experience with data engineering
• Possess profound knowledge of SQL, Spark and Python
• Solid experience with ETL, Kubernetes, Docker, Airflow and big data ecosystem
• Experience building and working with RESTful API Services
• Experience in cloud computing, machine learning and deep learning is a plus
• Great communication skills and fluent in English and Chinese, both written and spoken
• Understanding telecom industry and applications is an advantage
• Manage the enterprise analytics data platform and optimize the scalability and performance of the platform
• Act as a data architecture SME and provide advisory to data engineers and application teams for data architecture principles, standard and best practice
• Work closely with our data scientists to deliver world class data products and refactor code into reusable libraries, APIs or tools
• Use agile software development processes to iteratively make improvements to our back-end systems
• Model front end and back-end data sources to help draw a more comprehensive picture of user flows throughout our system and enable powerful data analysis
• Design, implement, test, deploy, and maintain stable, secure, and scalable data engineering solutions and pipelines in support of data and analytics projects, including integrating new sources of data into our enterprise analytics data platform, maintaining feature store, and moving data out to applications and affiliates
• Produce scalable, replicable code and engineering solutions that help automate repetitive data management tasks
• Collaborate with different stakeholders to Implement and ensure data governance model is in place on enterprise level
• Coaching junior staffs and take lead in new initiative
• Co-develop data analytics/technology roadmaps, and to correspondingly build and continue improve data architecture
Requirements
• Bachelor’s degree or above in Computer Science, Engineering or related fields
• Minimum 6 years of relevant experience with data engineering
• Possess profound knowledge of SQL, Spark and Python
• Solid experience with ETL, Kubernetes, Docker, Airflow and big data ecosystem
• Experience building and working with RESTful API Services
• Experience in cloud computing, machine learning and deep learning is a plus
• Great communication skills and fluent in English and Chinese, both written and spoken
• Understanding telecom industry and applications is an advantage
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