Data Architect

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips - the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world - like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.

What We Offer

Location:
Singapore,SGP

You'll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible-while learning every day in a supportive leading global company. Visit our Careers website to learn more.

At Applied Materials, we care about the health and wellbeing of our employees. We're committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.

Key Responsibilities:

• Design, build, and maintain scalable, reliable data pipelines to support AI/ML models and analytics in global supply chain and planning operations.
• Collaborate with data scientists and AI engineers to prepare and transform structured and unstructured data for modeling and simulation.
• Develop and optimize ETL/ELT processes using tools like Databricks, Spark.
• Ensure data quality, versioning, and lineage across the ML lifecycle.
• Support the deployment and monitoring of AI models in production environments.
• Translate business requirements into technical solutions, working closely with cross-functional teams.
• Contribute to the development of data services and APIs that power intelligent decision-making tools.

• 12-14 Years of strong experience in Data Architect roles
• Strong expertise in SQL, Python, and distributed data processing (e.g., Spark, PySpark).
• Experience with cloud-based data platforms (Azure).
• Familiarity with MLOps tools and practices (e.g., MLflow) is a strong advantage.
• Experience working with AI/ML frameworks (e.g., TensorFlow, PyTorch) or supporting model training and deployment is a strong advantage.
• Understands the role of data in driving supply chain and planning decisions.
• Able to align data engineering solutions with business KPIs and operational goals.
• May lead technical workstreams or mentor other engineers.
• Takes ownership of data infrastructure components and contributes to architectural planning.
• Solves complex data challenges with creativity and precision.
• Proactively identifies and resolves data quality, performance, and scalability issues.
• Enables the success of AI/ML initiatives by ensuring robust, scalable, and high-quality data infrastructure.
• Supports real-time and predictive decision-making across global operations.
• Communicates effectively with data scientists, AI engineers, and business stakeholders.
• Comfortable working in a fast-paced, collaborative environment with evolving priorities.