Enterprise Architect

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- Information Management Information Technology Atlas Copco Antwerp Belgium Hybrid

Job Description
/p h3Enterprise Architect – Information Management /h3 h3The role /h3 pThe 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. /p h3What you can expect from us /h3 ul liA friendly, family-like atmospherewith opportunities to develop and grow /li liA culture known for respectful interaction, ethical behavior and integrity /li liAn organization that uses diversity as a driver for performance /li liPotential to see your ideas realized and make an impact /li liNew challenges and new things to learn every day /li liAccess to global career opportunities, as part of the Atlas Copco Group /li /ul h3What we can expect from you /h3 h3Roles Responsibilities /h3 ul liDevelop and maintain the enterprise data architecture blueprint, covering different data domains, data products, flows, integrations, and lifecycle management. /li liEnable the creation of information architecture standards, metadata, taxonomy, ontology, and master data structures. /li liFacilitate consistency of data models across applications, platforms, and business units. /li liStimulate the design of data APIs, data products, and integration patterns. /li liFoster implementation of data governance frameworks, including ownership clarity, stewardship, and data quality processes. /li liDesign for architecture that enables AI/ML, including feature stores, vector databases, model registries, and ML-Ops pipelines. /li liDrive discussions cross the business areas to ensure data availability, quality, and governance. /li liPromote ethical, transparent, and responsible data and AI practices. /li liSupport and drive modernization initiatives such as instrumentation, data platform consolidation, and legacy system rationalization. /li liConduct architectural assessments, gap analyses, and technology evaluations for data use cases. /li liContribute architectural guidance and oversight for programs and investments in information management. /li liWork closely with business-IT leaders to translate strategic needs into data and AI capabilities. /li liPartner with data engineers, data scientists, product teams, and IT operations to ensure successful delivery. /li liFacilitate information management topics in architectural advisory boards and decision-making forums. /li liSupport innovation initiatives, proofs of concept, and emerging technology exploration. /li liDevelop 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. /li /ul h3Experience /h3 ul liRelevant experience in information architecture, enterprise architecture, or data management roles. /li liMaster’s degree in computer science, information Systems, Data Science, or equivalent experience. /li liProven experience designing enterprise scale data platforms. /li liStrong background in data modeling, integration patterns, and API driven architectures. /li liStrong understanding of ETL/ELT, data pipelines, streaming technologies, and event driven architectures. /li liExperience with AI/ML platforms, ML-Ops, and analytics ecosystems. /li liKnowledge of data governance tools, metadata management, and data cataloging. /li liEffective conceptualization and design-thinking skills. /li liAbility to present to management stakeholders and other business domains. /li liData-modeling and information classification at the enterprise level. /li liUnderstanding of metamodels, taxonomies and ontologies, as well as of the challenges of applying structured techniques (data modeling) to less-structured sources. /li liKnowledge of data architectures, data ingestion techniques, data storage, MDM, BI, and data warehouse design and implementation techniques. /li liKnowledge of problem analysis, structured analysis and design, and programming techniques. /li liAbility to analyze project, program and portfolio needs, as well as to determine the resources needed to achieve objectives and overcome cross-functional barriers. /li liProficiency with enterprise architecture tools (e.g. LeanIX is considered a plus). /li liCertifications such as TOGAF, DAMA CDMP, Azure/AWS Architect, or ITIL are a plus. /li liExperience with Master Data Management (M