Data Architect – Technology Architecture
Location: Hannemanns Allé 53, København S, Denmark
Job Overview
We are seeking an experienced and results‑driven Data Architect to partner with our Architecture, Engineering and Consulting Global Business Areas, aligning technology roadmap and strategies with business goals to drive growth and operational excellence.
Key Responsibilities
- Translate complex business requirements into secure, scalable data architectures aligned with enterprise strategy to unlock new revenue streams and optimise operational efficiency.
- Lead the design and implementation of modern, robust, and secure data systems using the contemporary data stack.
- Improve overall data quality and accessibility; define information and data architecture as part of the business and technology strategy.
- Design and implement integration solutions that connect disparate business systems and data sources for seamless data flow across the organisation.
- Support data platform teams by designing operating models that enable efficient data processing, integrations, reporting and AI model deployment.
- Design and develop data models that support business processes, analytics and reporting, optimizing for performance and scalability.
- Engage with technology providers to understand data‑relevant roadmaps, explore innovative solutions and evaluate alignment with business goals.
- Own and evolve Ramboll Tech’s enterprise data architecture, including principles, target‑state models, and standards.
- Establish, document, and enforce data architecture standards, modelling guidelines, and best practices across the organisation.
- Define and maintain enterprise and domain data models; shape data products, contracts, and interoperability patterns.
- Guide data platform usage across DWH, EDWH, Fabric, and analytics layers while ensuring integration points meet strict data protection standards across multi‑geo environments.
- Implement frameworks for data lineage, cataloging and automated observability to ensure trust and reliability in data pipelines.
- Maintain repositories of data elements, relationships, attributes, information flows and business glossary.
- Contribute to architectural governance by reviewing designs, guiding teams, and ensuring alignment with target architecture.
- Embed data quality, security and compliance (e.g., GDPR) into data integration pipelines.
- Collaborate closely with cross‑functional teams, including business stakeholders, product owners, data scientists, data engineers and SMEs.
- Operationalise data architecture and build robust, scalable technology stacks for digital and analytic solutions.
- Continuously evaluate and recommend new tools and technologies to improve efficiency and effectiveness of data engineering processes.
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Experience
- 5+ years of professional experience in data architecture, with a strong focus on cloud architecture, data integration and data modelling.
- Deep understanding of the modern data stack and its components.
- Prior engagement in establishing data architecture and data governance.
- Experience leading data modelling, database design, data warehousing, master data management and governance practices.
- Experience securing and protecting sensitive information.
- Experience in the AEC industry is advantageous.
- Developed data pipelines to extract, transform, load engineering platform data for analysis and reporting.
- Experience implementing decentralized data products within a Data Mesh architecture.
- Proven experience with cloud platforms such as Microsoft Azure, Google Cloud Platform or AWS.
Skills
- Exceptional analytical and problem‑solving skills with the ability to design innovative solutions to complex data challenges.
- Data modelling (conceptual, logical, physical), data warehousing, data lakes, data mesh, data governance, metadata management, master data management.
- Ability to lead the lifecycle of production‑grade data products from conceptual modelling to deployment and continuous optimization.
- Familiarity with the DAMA Data Management Framework (DAMA‑DMBOK).
- Understanding of engineering platforms and data integration with engineering systems.
- Advanced knowledge of data modelling tools, SQL and pipeline design.
- Excellent communication and interpersonal skills, conveying technical concepts to non‑technical stakeholders.
- Proficiency in Microsoft Fabric platform (advantage if available).
- Relevant certifications in cloud technologies, e.g., data engineering or Databricks certifications.