We are seeking an experienced Data and AI Cloud Architect to join our AWS Professional Services team in Taiwan. In this role, you will work directly with enterprise customers — particularly in the manufacturing and semiconductor industries — to design and implement modern data platforms, analytics solutions, and AI/ML workloads on AWS. You will serve as a trusted technical advisor, helping customers accelerate their cloud adoption journey and unlock business value from their data assets.
Key job responsibilities Key Responsibilities
- Lead the architecture design and delivery of data and AI solutions on AWS for strategic customers in Taiwan, with a focus on manufacturing and semiconductor verticals
- Design end-to-end data architectures including data lakes, data mesh, lakehouses, streaming analytics, and enterprise data warehouses using AWS services (e.g., Amazon S3, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Lake Formation)
- Architect and implement AI/ML solutions leveraging Amazon SageMaker, Amazon Bedrock, and other AWS AI services to address industry-specific use cases (predictive maintenance, yield optimization, defect detection, supply chain optimization)
- Collaborate with customers' technical and business stakeholders to define data strategies, roadmaps, and governance frameworks
- Lead technical workstreams within ProServe engagements, mentoring junior architects and consultants
- Develop reusable assets, frameworks, and best practices for Data & AI solution delivery within the manufacturing and semiconductor domains
- Partner with AWS account teams, solution architects, and specialist teams to identify and shape new customer opportunities
- Contribute to thought leadership through whitepapers, blog posts, reference architectures, and customer presentations
- Stay current with emerging AWS services and industry trends in data engineering, analytics, and generative AI
About the team AWS Professional Services works with enterprise customers and partners to help them realize their desired business outcomes through cloud adoption. Our team assists customers in achieving the greatest value from AWS by providing guidance, best practices, and hands-on delivery support throughout their cloud journey.
Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
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Basic Qualifications
- Experience conveying complex technical concepts to both technical and business audiences
- Bachelor's degree or above in computer science, computer engineering, or related field, or Bachelor's degree and 1+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 8+ years of experience in data engineering, data architecture, or cloud architecture, with 5+ years hands-on designing and implementing data solutions on AWS or other major cloud platforms
- Deep expertise in data platform technologies: data lakes, data warehouses, ETL/ELT pipelines, streaming architectures, and data governance, with proficiency in Python, SQL, Spark, or Scala
- Fluency in Mandarin Chinese and English (written and verbal)
Preferred Qualifications
- Experience with large scale IT/digital/business transformation or migration programs in a customer facing role
- Domain expertise in manufacturing and/or semiconductor industries — understanding of fab operations, MES/ERP integration, equipment health monitoring, yield management, process control (SPC/FDC), supply chain digitization, and semiconductor-specific data challenges (high-volume time-series data, wafer-level analytics, APC, predictive maintenance)
- Experience with Industry 4.0 / Smart Manufacturing initiatives including IoT, digital twin, edge-to-cloud architectures, and OT/IT convergence for industrial data integration
- Experience with generative AI architectures including RAG patterns, foundation model fine-tuning, and AI agents
- Familiarity with data privacy and compliance requirements in the Taiwan market
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