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ASM International

Semiconductor deposition equipment and ALD tech

Principal Engineer - Data, Bia & AI

Data ManagementConfirmed live in the last 24 hours
Full-timePhoenix, AZ, USANo salary listedIn-person

About the Job

Requirements

  • A degree in data science, information technology, computer science, mathematics, engineering, business administration, or a related field is required.
  • Seven or more years of data architecture and solutioning experience are required.
  • Strong hands-on experience in multiple data and analytics competency areas, such as data products, lakehouse architecture, data engineering, business intelligence, semantic models, data governance, and data quality, is required.
  • Strong understanding of data engineering concepts and technologies, including SQL, Python, Spark-based processing, orchestration, and metadata-driven engineering, is required.
  • Strong understanding of data governance, metadata management, cataloging, lineage, data contracts, data quality, classification, access control, retention, auditability, and responsible AI principles is required.
  • Ability to work with complex and diverse structured, semi-structured, unstructured, streaming, sensor, equipment, and operational data is required.
  • Experience with Databricks and cloud platforms such as AWS, Azure, or Google Cloud is required.
  • A drive to understand business operations and commercial products is required.
  • Ability to collaborate and coordinate with multiple teams, stakeholders, and external partners is required.
  • Stakeholder engagement and communication skills to explain complex technical topics to business leaders, product teams, engineers, and others are required.
  • Coaching and influencing skills to guide architecture decisions, mentor technical teams, facilitate design discussions, and build data architecture maturity are required.
  • An outcome-driven focus on business value, adoption, reuse, scalability, speed, cost efficiency, and measurable impact is required.

Responsibilities

  • Define and govern ASM’s Enterprise Data Architecture Framework, including reference architecture, standards, guardrails, and reusable playbooks.
  • Define how platforms such as Databricks, SAP, Teamcenter, Salesforce, and Celonis fit together in ASM’s target data architecture.
  • Drive architectural consistency, reuse, and simplification across data platforms and business domains.
  • Identify and reduce data architecture debt, duplicate capabilities, inconsistent data models, and unnecessary platform fragmentation.
  • Lead architecture and peer reviews to ensure solution designs follow enterprise data architecture standards and deliver measurable business impact.
  • Define architectural patterns for data products, integration, interoperability, and data sharing across domains.
  • Design trusted data foundations for analytics, business intelligence, machine learning, generative AI, agentic AI, process intelligence, and automation use cases.
  • Design scalable, secure, reusable, and cost-effective data architectures across lakehouse, warehouse, data lake, streaming, near-real-time, event-driven, operational, and analytical platforms.
  • Embed security and compliance by design, including classification, retention, trade compliance, and access, in partnership with Cyber Security, AI Governance, Enterprise Architecture, and Legal.
  • Ensure architecture-by-design for data quality, consistency, accuracy, completeness, lineage, integrity, observability, auditability, and explainability across all layers.
  • Partner with manufacturing, supply chain, engineering, quality, services, and other teams to translate priorities into scalable solutions.
  • Work with Digital Transformation Business Partners to translate business outcomes, process needs, analytical needs, and value opportunities into scalable and reusable data architecture solutions.
  • Ensure architecture decisions are practical for teams to adopt, including through documentation and reusable templates.
  • Support establishing the vision for managing data as a business asset and maximizing the return on data assets.
  • Evaluate emerging technologies and industry trends to continuously evolve ASM’s data and AI capabilities.
  • Support fostering a data-driven culture, related competencies, and data literacy across ASM.

Desired Qualifications

  • Relevant professional training or certifications are desired but not required.
  • Certifications in Databricks, data architecture, enterprise architecture, data management, AI/ML platforms, data governance, or Agile are preferred but not required.
  • Experience with Teamcenter, Salesforce, SAP systems such as SAP S/4HANA, Celonis, Incorta, or Microsoft Power BI is desired.
  • Experience working in a semiconductor or high-tech manufacturing environment is desired.

About the Company

ASM International

Semiconductor deposition equipment and ALD tech

ASM International designs and supplies equipment and technologies for semiconductor fabrication, focusing on thin-film deposition processes such as chemical vapor deposition (CVD) and atomic layer deposition (ALD). Its products are used in making microchips by depositing ultra-thin material layers with precise control at the atomic level, enabling smaller and more powerful devices. The company built a global footprint through operations in the Netherlands, the US, Hong Kong, and Japan, and separated ASML Lithography (a joint venture with Philips) to focus on deposition while ASML develops photolithography systems. In recent years, ASM has sharpened its strategy around ALD, a process that creates uniformly thin layers one atomic layer at a time, allowing continued scaling of semiconductor devices. The goal is to be a core supplier of deposition technology and tools that enable chip manufacturers to produce smaller, faster, and more energy-efficient semiconductors.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Almere, Netherlands
Founded
1968

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