Enterprise Architect

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Enterprise Architect – Information Management

The role

The Enterprise Architect - Information Management plays a key role in enterprise-wide data and information architecture, ensuring that the cross-business area organization’s data landscape is coherent, secure, high quality and usable for advanced analytics and AI adoption. This role contributes to and evolves the long ‑ term data strategy, drives architectural standards, and ensures that data becomes a strategic asset powering business value, automation, and AI enabled decision making. In alignment with Atlas Copco’s decentralized operating model, this role focuses on building collaborative relationships and delivering results through partnerships.

What you can expect from us

• A friendly, family-like atmospherewith opportunities to develop and grow
• A culture known for respectful interaction, ethical behavior and integrity
• An organization that uses diversity as a driver for performance
• Potential to see your ideas realized and make an impact
• New challenges and new things to learn every day
• Access to global career opportunities, as part of the Atlas Copco Group

What we can expect from you

Roles & Responsibilities

• Develop and maintain the enterprise data architecture blueprint, covering different data domains, data products, flows, integrations, and lifecycle management.
• Enable the creation of information architecture standards, metadata, taxonomy, ontology, and master data structures.
• Facilitate consistency of data models across applications, platforms, and business units.
• Stimulate the design of data APIs, data products, and integration patterns.
• Foster implementation of data governance frameworks, including ownership clarity, stewardship, and data quality processes.
• Design for architecture that enables AI/ML, including feature stores, vector databases, model registries, and ML-Ops pipelines.
• Drive discussions cross the business areas to ensure data availability, quality, and governance.
• Promote ethical, transparent, and responsible data and AI practices.
• Support and drive modernization initiatives such as instrumentation, data platform consolidation, and legacy system rationalization.
• Conduct architectural assessments, gap analyses, and technology evaluations for data use cases.
• Contribute architectural guidance and oversight for programs and investments in information management.
• Work closely with business-IT leaders to translate strategic needs into data and AI capabilities.
• Partner with data engineers, data scientists, product teams, and IT operations to ensure successful delivery.
• Facilitate information management topics in architectural advisory boards and decision-making forums.
• Support innovation initiatives, proofs of concept, and emerging technology exploration.
• Develop a comprehensive view of the Group IT data landscape by identifying core data objects, analyzing their usage across systems and business areas, and establishing transparency on ownership and consumption.

Experience

• Relevant experience in information architecture, enterprise architecture, or data management roles.
• Master’s degree in computer science, information Systems, Data Science, or equivalent experience.
• Proven experience designing enterprise scale data platforms.
• Strong background in data modeling, integration patterns, and API driven architectures.
• Strong understanding of ETL/ELT, data pipelines, streaming technologies, and event driven architectures.
• Experience with AI/ML platforms, ML-Ops, and analytics ecosystems.
• Knowledge of data governance tools, metadata management, and data cataloging.
• Effective conceptualization and design-thinking skills.
• Ability to present to management stakeholders and other business domains.
• Data-modeling and information classification at the enterprise level.
• Understanding of metamodels, taxonomies and ontologies, as well as of the challenges of applying structured techniques (data modeling) to less-structured sources.
• Knowledge of data architectures, data ingestion techniques, data storage, MDM, BI, and data warehouse design and implementation techniques.
• Knowledge of problem analysis, structured analysis and design, and programming techniques.
• Ability to analyze project, program and portfolio needs, as well as to determine the resources needed to achieve objectives and overcome cross-functional barriers.
• Proficiency with enterprise a