Data Engineer Jobs

About The Position

Requirements

• A degree in data science, information technology, computer science, mathematics, engineering, business administration, or a related field.
• 7+ years of data architecture and solutioning experience.
• Strong hands-on experience in multiple competency areas related to data and analytics, such as data products, lakehouse architecture, data engineering, business intelligence, semantic models, data governance, and data quality.
• Strong understanding of data engineering concepts and technologies, including SQL, Python, Spark-based processing, orchestration and metadata-driven engineering
• Strong understanding of data governance, metadata management, cataloging, lineage, data contracts, data quality, classification, access control, retention, auditability, and responsible AI principles.
• Ability to work with complex and diverse data sources, including structured, semi-structured, unstructured, streaming, sensor, equipment, and operational data.
• Experience in Databricks and cloud platforms (e.g. AWS/Azure/Google Cloud).
• A drive to understand our business operations and commercial products.
• Action-oriented mindset, with the ability to move quickly while maintaining architecture discipline and governance.
• Able to collaborate and coordinate with multiple teams, stakeholders and external partners.
• Excellent stakeholder engagement and communication skills, with the ability to explain complex technical topics to business leaders, product teams, engineers, and others.
• Good coaching and influencing skills, with the ability to guide architecture decisions, mentor technical teams, facilitate design discussions, and build data architecture maturity across ASM.
• Outcome-driven mindset with focus on business value, adoption, reuse, scalability, speed, cost efficiency, and measurable impact.

Nice To Haves

• Relevant professional training or certifications are desired but not required.
• Relevant certifications in Databricks, data architecture, enterprise architecture, data management, AI/ML platforms, data governance, or Agile are preferred, but not required.
• Experience in Teamcenter, Salesforce, SAP systems (e.g. SAP S4 HANA), Celonis, Incorta, or Microsoft PowerBI
• Experience working in a semiconductor or high-tech manufacturing environment.

Responsibilities

• Own ASM’s Data Architecture: Define and govern ASM's Enterprise Data Architecture Framework, including reference architecture, standards, guardrails and reusable playbooks.
• Define how key platforms such as Databricks, SAP, Teamcenter, Salesforce and Celonis fit together in ASM’s target data architecture.
• Drive architectural consistency, reuse and simplification across all data platforms and business domains.
• Identify and reduce data architecture debt, duplicate capabilities, inconsistent data models and unnecessary platform fragmentation.
• Lead architecture reviews, and peer reviews to ensure solution designs follow enterprise data architecture standards and deliver measurable business impact.
• Design Trusted and AI-Ready Data Foundations: Define architectural patterns for data products, integration, interoperability and data sharing across domains.
• Design trusted data foundations supporting analytics, business intelligence, machine learning, GenAI, 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 (classification, retention, trade compliance, access etc.) in partnership with Cyber Security, AI Governance, Enterprise Architecture and Legal.
• Ensure architecture-by-design for data quality, consistency, accuracy, completeness, lineage, observability, auditability, and explainability across all layers.
• Partner, Influence and Innovate: 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 to adopt by the various teams, including documentation, and reusable templates.
• Be a Subject Matter Expert: Support the establishing of the vision for managing data as a business asset, and to maximize the return on data assets.
• Evaluate emerging technologies and industry trends to continuously evolve ASM's data and AI capabilities.
• Support the fostering of the creation of a data-driven culture, related competencies and data literacy across ASM.

Benefits

• development programs help support your growth, shaping your future and pushing the boundaries of innovation to unleash potential.