Cloud Data Engineer – Taiwan

Part of The Brandtech Group, fifty-five is a data consultancy helping brands collect, analyse and activate their data across paid, earned and owned channels to increase their marketing ROI and improve customer experience. As a Cloud Data Engineer, you will design and implement data architectures and pipelines for cloud and digital analytics projects on cloud platforms.

Requirements

• University degree in Computer Science, Information Systems, or related disciplines
• Minimum 1 year of experience with cloud data platforms (GCP preferred; AWS or Azure also welcome)
• Familiar with data engineering concepts and tools (e.g. BigQuery, Dataflow, Pub/Sub, Airflow, etc.)
• Proficient in one or more programming languages (e.g. Python, Java)
• Knowledge of API design, microservices, and DevOps practices (CI/CD, version control, containerization)
• Good understanding of data analytics, data warehousing, and visualization (e.g. Looker, Data Studio, Tableau)
• Experience with website or mobile app tracking implementation is a plus
• Professional cloud certification (GCP, AWS, or Azure) is a plus
• Able to communicate technical concepts clearly to non-technical stakeholders
• Strong problem-solving skills, self-driven, and collaborative
• Fluent in English and Mandarin Chinese

Benefits

• Exposure to cloud automation, marketing platforms, and media data analytics projects
• Opportunity to work with our global consulting and engineering teams to engage our clients from diverse industries around the world
• 20 days Annual Leave
• Work remotely (Maximum 2 days a week Work From Home policy)
• Regular team activities including TGIF, team lunch and Off-site!
• A multicultural environment with employees from over 20 countries
• Values centered on excellence, caring and sharing
• Continuous (and certified) training on the digital ecosystem and technologies
• Particular importance given to work-life balance and the right to disconnect
• Work-life balance and strong support for well-being
• The opportunity of taking part in internal projects such as The Data Hive or Women@55