Data Architect

Requirements

• At least 5 years of proven experience as a Data Architect or a similar role, with a strong track record of designing and delivering enterprise-scale data models in complex, multi-stakeholder environments;
• More than 10 years proven practical expertise in data modeling (conceptual, logical, and ideally physical), with demonstrated ability to make models implementable across both business and IT, bridging semantic clarity with technical precision;
• Experience in data quality, lifecycle management and its implication on data architecture, data governance, including the implementation and operationalization of platforms to monitor, measure, and enforce data standards at scale;
• Strong understanding of how technology and data are interconnected, including data integration patterns, API design, and the role of data architecture within the broader enterprise technology landscape;
• Demonstrated ability to deliver large-scale, complex projects in demanding business environments, with accountability for end-to-end outcomes across architecture, implementation, and adoption;
• Understanding of how AI can impact the data architecture space, including implications for data modeling, lineage, quality, and governance;
• Excellent collaboration and stakeholder management skills, with the ability to work effectively across business lines and influence senior stakeholders toward aligned, firm-wide outcomes;
• Clear and confident communicator, able to translate complex data concepts into concise, audience-appropriate language for both technical and non-technical stakeholders;
• Experience in financial services and/or asset management is an advantage;
• Excellent English oral and written communication skills; German is a plus.
• What you can expect
• We provide modern working conditions , including work-from-home options, flexible hours and a home office allowance to ensure staff members have a work environment equipped with the latest technology;
• A diverse culture founded on mutual respect, teamwork and appreciation awaits you at LGT Capital Partners. We go the extra mile to generate impact;
• We are proud to be owned by the Princely Family of Liechtenstein and our company is inspired by its entrepreneurial spirit;
• Commitment to ESG: our approach to business is influenced by the Princely Family's long-term perspective. Sustainability is key for us and has shaped our actions since 2002;
• You benefit from favorable terms and conditions if you wish to participate in LGT Capital Partners' investment

Benefits

Additional Information

Job Description Within the Solution Architecture and Engineering IT organization, we are looking for an experienced Data Architect to drive the firm-wide definition and adoption of enterprise data capabilities, spanning data modeling, data ownership, and contributing to data governance, ensuring data is structured and consistently understood across the organizations. This role offers the opportunity to make a tangible, firm-wide impact, with real ownership to shape how data is understood, governed, and leveraged across the company. The Data Architect will play a key role in enabling business-critical initiatives by establishing a coherent enterprise data model, contributing to drive data quality and governance at scale, and bridging the gap between business semantics and technical implementation across systems and interfaces. The key tasks include: Drive the definition of an enterprise-wide data model in close collaboration with business units and key stakeholders, as well as lead its implementation across core systems and interfaces in coordination with relevant IT organizations. Ensure the model is both architecturally sound and practically adoptable across business and technology teams; Lead the firm-wide discussion on data mastership, identifying authoritative data sources, resolving ambiguities, and defining a clear target landscape for how data is managed and maintained, covering the fully data lifecycle; Significantly contribute to the firm's data quality and governance strategy, including the implementation of platforms and tooling to monitor, measure, and enforce data quality standards in a scalable and sustainable way; Design and evolve the overall data architecture landscape, ensuring alignment between business data needs and the technical systems, platforms, and interfaces that serve them, including data warehouses, data lakes, APIs, and integration layers; Continuously assess emerging technologies and approaches in the data space, including AI-driven data modeling and management, metadata platforms, and automated governance tooling, identifying opportunities to enhance the firm's data modeling capabilities.

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