Data Architect - Global Data & Analytics Platform
Alfa Laval Technologies AB · Lund · Tills vidare · Deadline 2026-11-17
Alfa Laval Technologies AB is seeking a **Data Architect - Global Data & Analytics Platform** to shape the technical foundation across its global business domains, including R&D, sales, finance, operations, and sustainability. The role balances strategic architecture with **hands-on data modelling**, assessing the current distributed systems and establishing a unified target architecture and roadmap. Working alongside business stakeholders, architects, data engineers, and developers, you will define architectural principles, guardrails, and consistent data models to ensure data across ERP, CRM, and domain solutions is secure, reusable, and optimized for reporting, digital products, and AI. Applicants must have at least five years of experience in data architecture, enterprise data architecture, data platform architecture, or an equivalent senior data role. **Extensive enterprise data architecture experience** in conceptual, logical, and physical data modelling is required, as is practical knowledge of designing cloud-based platforms, integration patterns, data governance, and distributed paradigms like data mesh. Candidates need hands-on competence with tools such as Databricks, Unity Catalog, SQL, Python or PySpark, and Power BI, or similar technologies, paired with fluent written and spoken English. Prior experience in global matrixed organizations, enterprise platforms on Microsoft Azure, or domain areas such as manufacturing, supply chain, and CRM is advantageous.
About the job
As a Data Architect, you will shape the future architecture of Alfa Laval's Global Data & Analytics Platform. You will work across business domains, source systems, data products and technical teams to create a connected, scalable and governed data landscape. Combining strategic architecture with hands-on data modelling, you will assess the current landscape, define the target architecture and help teams bridge the gap between the current and future states.
Alfa Laval's global data landscape spans research and development, sales, service, operations, supply chain, finance, HR and sustainability, with data distributed across multiple source systems and structures. You will collaborate with business stakeholders, enterprise and solution architects, data product teams, developers and platform engineers to establish common standards, models and architectural principles. Your work will make enterprise data easier to find, understand, integrate and reuse, creating a scalable foundation for reporting, analytics, digital products and AI.
Key responsibilities
- Define and drive a coherent data architecture for Alfa Laval's Global Data & Analytics Platform-creating one connected architectural direction across business domains, systems, products and value streams, including ERP, CRM and domain-specific solutions.
- Establish and promote common architectural principles, standards and guardrails for data modelling, governance, integration, interoperability, security, quality, scalability and reuse across the platform.
- Shape the target architecture and roadmap by assessing the current landscape, identifying gaps and dependencies, and defining practical steps towards a unified future state.
- Create and maintain consistent, reusable data models across business domains, supporting common definitions and enabling data to be used across multiple analytics and business use cases.
- Translate business requirements into enterprise-level data architecture, ensuring that data products and platform capabilities align with the overall architecture rather than creating isolated solutions.
- Work hands-on with architects, data engineers and developers to implement data models, integration patterns and shared platform capabilities.
- Partner with business and technical stakeholders to align priorities, explain architectural decisions, resolve trade-offs and build support across organizational boundaries.
- Collaborate with other architects and evaluate technologies to ensure the platform can support future analytics, AI and digital business needs.
Who are you
You are a strategic and hands-on data architect who is comfortable working with ambiguity, navigating complex organizations and making decisions with incomplete information. You are pragmatic and structured, with a focus on implementable outcomes and long-term business value. Rather than creating isolated solutions, you are motivated by building reusable capabilities that can support the organization over time. You are curious and forward-looking, while remaining grounded in practical delivery.
You build strong working relationships with business and technical stakeholders and are comfortable working with people at different levels and in different disciplines. You explain complex architectural topics clearly and practically, facilitate discussions, create alignment across organizational silos, and use communication and influencing skills to drive change. You are collaborative and approachable, while also being prepared to constructively challenge existing assumptions and approaches when this helps create better outcomes across a global, matrixed organization.
What you know
To succeed in this role, you bring strong experience in data architecture and modelling, combined with the technical expertise needed to shape and implement scalable cloud-based data platforms. We believe you have:
- At least five years of experience in data architecture, enterprise data architecture, data platform architecture or a related senior data role.
- Proven experience designing and implementing modern cloud-based data and analytics architectures in enterprise environments, preferably using Microsoft Azure and Azure data services.
- Strong experience in conceptual, logical and physical data modelling, including translating business requirements into data architecture and implementable data models.
- Ability to balance platform standardization with domain autonomy, enabling reusable data products while supporting business-specific needs.
- Experience designing data integration, transformation and orchestration solutions, including enterprise integration patterns and cross-system data flows.
- Experience defining target architecture, architectural principles, standards and implementation roadmaps.
- Experience working with enterprise data platforms, data products, including data mesh or similar distributed data concepts.
- Hands-on experience with Databricks, Unity Catalog, SQL, Python/PySpark and Power BI, or similar tools.
- Experience with data governance, access models, data quality, metadata management and data security.
- Experience working across multiple business domains, products or value streams.
- Experience working with both technical delivery teams and senior business stakeholders.
- Fluent English, both written and spoken.
It is considered an advantage if you have:
- Experience working across business domains such as ERP, CRM, supply chain, finance or manufacturing.
- Experience supporting analytics, machine learning or AI use cases.
- Experience with cloud-based data platforms, particularly Microsoft Azure.
- Experience in a large, global and matrixed organization.