📍 Job Overview

• Job Title: Cloud Data Engineer - Taiwan
• Company: Fifty-Five
• Location: Taipei, Taiwan
• Job Type: Hybrid (3 days on-site)
• Category: Data Engineering
• Date Posted: 2025-08-01
• Experience Level: Entry to Mid-Level (0-2 years)
• Remote Status: Hybrid (Taipei-based)

🚀 Role Summary

• Design and implement data architectures and pipelines for cloud and digital analytics projects on cloud platforms.
• Deliver hands-on technical services including cloud migration, data transformation, data warehousing, visualization, and advanced analytics.
• Set up CI/CD pipelines and deployment workflows to ensure proper integration of cloud infrastructure and data pipelines.
• Streamline and automate processes to optimize performance and cost-efficiency for digital analytics platforms.
• Support pre-sales activities with local consultants and collaborate with the global engineering team to develop and deliver POCs for cloud and data-related use cases.

📝 Enhancement Note: This role requires a strong foundation in cloud data platforms and data engineering concepts, with a focus on GCP but open to AWS or Azure experience. The ideal candidate will have a good understanding of data analytics, data warehousing, and visualization tools, and be able to communicate technical concepts clearly to non-technical stakeholders.

💻 Primary Responsibilities

• Cloud Architecture & Pipeline Design: Design and implement data architectures and pipelines for cloud and digital analytics projects on cloud platforms, with a focus on GCP but open to AWS or Azure experience.
• Hands-On Technical Services: Deliver hands-on technical services including cloud migration, data transformation, data warehousing, visualization, and advanced analytics to support clients in Taiwan and the region.
• CI/CD Pipeline & Deployment Workflows: Set up CI/CD pipelines and deployment workflows to ensure proper integration of cloud infrastructure and data pipelines, optimizing performance and cost-efficiency for digital analytics platforms.
• Process Automation: Streamline and automate processes to optimize performance and cost-efficiency for digital analytics platforms, enabling better decision-making and improved customer experience.
• Pre-Sales Support & POC Development: Support pre-sales activities with local consultants by contributing to demos, RFPs, and technical solutioning. Collaborate with the global engineering team to develop and deliver POCs for cloud and data-related use cases.

📝 Enhancement Note: This role requires a strong problem-solving mindset, with the ability to work independently and collaborate effectively with cross-functional teams. The ideal candidate will be self-driven, proactive, and able to adapt to new technologies and tools as needed.

🎓 Skills & Qualifications

Education: A university degree in Computer Science, Information Systems, or a related discipline is required.

Experience: A minimum of 1 year of experience with cloud data platforms (GCP preferred; AWS or Azure also welcome) is required. Familiarity with data engineering concepts and tools, as well as proficiency in one or more programming languages (e.g., Python, Java), is essential.

Required Skills:

• Cloud data platforms (GCP, AWS, or Azure)
• Data engineering concepts and tools (e.g., BigQuery, Dataflow, Pub/Sub, Airflow)
• Programming languages (e.g., Python, Java)
• API design, microservices, and DevOps practices (CI/CD, version control, containerization)
• Data analytics, data warehousing, and visualization tools (e.g., Looker, Data Studio, Tableau)
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders
• Problem-solving skills, self-driven, and collaborative

Preferred Skills:

• Experience with website or mobile app tracking implementation
• Professional cloud certification (GCP, AWS, or Azure)
• Familiarity with marketing data analytics and customer data platforms

📝 Enhancement Note: While not required, experience with marketing data analytics and customer data platforms can be beneficial for this role, as fifty-five specializes in helping brands collect, analyze, and activate their data across paid, earned, and owned channels to increase marketing ROI and improve customer experience.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

• Demonstrate your experience with cloud data platforms, data engineering concepts, and tools through relevant projects and case studies.
• Showcase your ability to design and implement data architectures and pipelines, as well as deliver hands-on technical services, including cloud migration, data transformation, data warehousing, visualization, and advanced analytics.
• Highlight your problem-solving skills and ability to optimize performance and cost-efficiency for digital analytics platforms.

Technical Documentation:

• Provide clear and concise documentation for your projects, including data flow diagrams, architecture overviews, and code comments.
• Explain your approach to data transformation, data warehousing, and advanced analytics, and how you ensured data quality and accuracy.
• Describe the CI/CD pipelines and deployment workflows you implemented to ensure proper integration of cloud infrastructure and data pipelines.

📝 Enhancement Note: As this role requires strong communication skills and the ability to explain technical concepts to non-technical stakeholders, it is essential to include clear and concise documentation that can be easily understood by both technical and non-technical team members.

💵 Compensation & Benefits

Salary Range: NT$700,000 - NT$1,200,000 per year (Based on experience and market research for cloud data engineers in Taiwan)

Benefits:

• Exposure to cloud automation, marketing platforms, and media data analytics projects
• Opportunity to work with global consulting and engineering teams, engaging with clients from diverse industries around the world
• 20 days of annual leave
• Hybrid work arrangement (maximum 2 days a week working from home)
• Regular team activities, including TGIF, team lunch, and off-site events
• 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
• Support for well-being and participation in internal projects, such as The Data Hive and Women@55

🎯 Team & Company Context

Company Culture:

• Industry: Data consultancy focused on helping brands collect, analyze, and activate their data across paid, earned, and owned channels to increase marketing ROI and improve customer experience.
• Company Size: Medium-sized (10 offices worldwide, with around 500 employees)
• Founded: 2010, with a strong focus on data-driven strategies, optimized customer engagement, and automated marketing solutions.

Team Structure:

• Work closely with local and global engineering teams, as well as local consultants, to deliver cloud and data-related projects for clients in Taiwan and the region.
• Collaborate with cross-functional teams, including data scientists, data analysts, and marketing specialists, to ensure data-driven decision-making and improved customer experience.

Development Methodology:

• Agile development methodologies, with a focus on continuous integration, continuous delivery, and continuous improvement.
• Regular code reviews, testing, and quality assurance practices to ensure data accuracy and reliability.
• Deployment strategies, CI/CD pipelines, and server management to optimize performance and cost-efficiency for digital analytics platforms.

Company Website: www.fifty-five.com

📝 Enhancement Note: Fifty-Five encourages diversity and is committed to guaranteeing equal treatment of all applications, regardless of gender, age, origin, sexual orientation, state of health, or political or religious opinion. This commitment to diversity and inclusion creates a supportive and collaborative work environment for employees from all backgrounds.

📈 Career & Growth Analysis

Web Technology Career Level: Entry to Mid-Level (0-2 years) Cloud Data Engineer, with a focus on designing and implementing data architectures and pipelines, delivering hands-on technical services, and optimizing performance and cost-efficiency for digital analytics platforms.

Reporting Structure: This role reports directly to the Engineering Manager for the Taipei office and works closely with local and global engineering teams, as well as local consultants, to deliver cloud and data-related projects for clients in Taiwan and the region.

Technical Impact: As a Cloud Data Engineer at Fifty-Five, you will have a significant impact on the company's ability to deliver data-driven solutions for clients, enabling better decision-making, improved customer experience, and increased marketing ROI. Your work will directly contribute to the success of Fifty-Five's clients and the growth of the company as a whole.

Growth Opportunities:

• Technical Skill Development: Fifty-Five offers continuous (and certified) training on the digital ecosystem and technologies, providing opportunities for professional growth and development in cloud data engineering.
• Technical Leadership: With experience and proven performance, there may be opportunities to take on more senior roles within the engineering team, such as a Senior Cloud Data Engineer or Technical Lead.
• Global Exposure: As part of the global engineering team, you will have the opportunity to work with clients from diverse industries around the world, gaining valuable experience and insights into global data trends and best practices.

📝 Enhancement Note: Fifty-Five's commitment to continuous learning and professional development, combined with its global presence and diverse client base, creates numerous opportunities for growth and advancement within the company.

🌐 Work Environment

Office Type: Modern, collaborative workspace designed to foster innovation and creativity, with state-of-the-art technology and tools to support data engineering projects.

Office Location(s): Taipei, Taiwan, with additional offices in Paris, London, New York City, Hong Kong, Shenzhen, Shanghai, and Singapore.

Workspace Context:

• Collaborative Workspace: Fifty-Five's offices are designed to encourage collaboration and teamwork, with open-plan workspaces, meeting rooms, and breakout areas for informal discussions and brainstorming sessions.
• Technology & Tools: Employees have access to the latest technology and tools to support their work, including high-performance workstations, multiple monitors, and testing devices.
• Cross-Functional Collaboration: Fifty-Five's teams are composed of individuals with diverse skills and backgrounds, fostering a culture of collaboration and knowledge-sharing across disciplines.

Work Schedule: A standard workweek of 40 hours, with flexible working hours to accommodate project deadlines and maintenance windows. Fifty-Five offers a hybrid work arrangement, with a maximum of 2 days per week working from home.

📝 Enhancement Note: Fifty-Five's commitment to work-life balance and the right to disconnect ensures that employees have the time and resources they need to maintain a healthy work-life balance, promoting well-being and job satisfaction.

📄 Application & Technical Interview Process

Interview Process:

1. Technical Assessment: A hands-on technical assessment, focusing on cloud data platforms, data engineering concepts, and tools, as well as programming languages and problem-solving skills.
2. Behavioral Interview: A discussion of your problem-solving skills, communication skills, and ability to work effectively with cross-functional teams.
3. Final Interview: A meeting with the Engineering Manager to discuss your career goals, fit within the team, and next steps in the interview process.

Portfolio Review Tips:

• Project Selection: Choose projects that demonstrate your experience with cloud data platforms, data engineering concepts, and tools, as well as your ability to design and implement data architectures and pipelines.
• Case Study Structure: Present your projects using a structured case study format, including an overview of the project, your role and responsibilities, the challenges you faced, and the solutions you implemented.
• Code Quality: Ensure that your code is well-documented, with clear comments and consistent formatting, demonstrating your attention to detail and commitment to data quality and accuracy.
• Company-Specific Considerations: Familiarize yourself with Fifty-Five's focus on data-driven strategies, optimized customer engagement, and automated marketing solutions, and highlight how your projects align with these priorities.

Technical Challenge Preparation:

• Technical Exercise Format: Prepare for a technical exercise that focuses on cloud data platforms, data engineering concepts, and tools, as well as programming languages and problem-solving skills.
• Time Management: Practice time management techniques to ensure that you can complete the technical exercise within the allotted time frame.
• Communication & Explanation: Rehearse your explanations of technical concepts and approaches, ensuring that you can clearly and concisely articulate your thought processes and decision-making strategies.

ATS Keywords:

• Programming Languages: Python, Java, SQL, BigQuery, Dataflow, Pub/Sub, Airflow
• Cloud Data Platforms: GCP, AWS, Azure
• Data Engineering Tools: BigQuery, Dataflow, Pub/Sub, Airflow, Cloud Composer, Cloud Data Fusion, Cloud DataProc, Cloud DataPrep, Cloud Pub/Sub, Cloud Storage, Google Cloud Functions, Google Cloud Run, Google Kubernetes Engine, Google Cloud Endpoints, Google Cloud APIs, Google Cloud IAM, Google Cloud SDK, Google Cloud Console, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell, Google Cloud Shell