Data Architect

About the role: We're looking for a hands-on Data Platform Architect to own the architecture, delivery, and governance of Auditdata's group-wide data platform, built on Azure. You'll design and build a single, reliable analytical ecosystem that consolidates data from multiple Auditdata products — starting with Practice Management Software — across countries and regions, powering reporting, analytics, and data-driven decision-making group-wide. This role combines strategic ownership with hands-on execution: you'll set the architectural direction and also build it yourself. Two early mandates will define your first months: Define the target data platform strategy within the Azure ecosystem (Azure SQL, Synapse, Microsoft Fabric/OneLake) and own the roadmap from current state to target architecture. Design the cross-product consolidation architecture — establishing how data from independently built products, spanning different regions and legal jurisdictions, converges into a single governed platform. What you'll do: Data Platform Architecture: Define and evolve the group data platform architecture - evaluate and select the target Azure stack (Azure SQL, Synapse, Fabric) and own the migration roadmap to it. Design the multi-source integration architecture: ingestion from multiple products with heterogeneous schemas, using an integration-layer pattern suited to many sources (medallion/lakehouse or Data Vault) beneath a dimensional serving layer. Address multi-region and data residency requirements: regional hosting, cross-border transfer constraints, GDPR and local privacy law, tenant and country-level data isolation. Collaborate with Infrastructure Architects on storage, compute, performance, and Azure cost optimization across regions. Data Modeling & Master Data: Design and maintain the three modeling layers: raw/integration (multi-source harmonization), canonical/master data (shared entities such as clinic, patient, device, product across products and countries), and serving (Kimball fact/dimension models optimized for Power BI). Define master data management approach: entity matching, survivorship, and golden-record rules across products. Optimize analytical models for performance (incremental refresh, partitioning, query tuning). Data Engineering (hands-on): Design, build, and maintain ETL/ELT pipelines consolidating data from product services into the platform. Build and tune Power BI semantic models and support dashboard development. Implement data quality, lineage, and observability - monitoring, alerting, reconciliation checks across sources. Integration & Governance: Collaborate with Domain Architects and product teams to define data contracts and export interfaces from operational services. Govern data ingestion - accuracy, performance, and alignment with security and privacy policies. Establish and run group data governance: ownership, definitions (a shared business glossary across products), metadata management, documentation, and schema versioning. Contribute to ADRs, data architecture diagrams, and data governance documentation. Data Migration (secondary): Support customer data migration into Manage from legacy systems - mapping, transformation, and validation approaches. Define reusable migration tooling and quality gates in collaboration with onboarding/delivery teams. Stakeholders: Work with business stakeholders across products and countries to translate analytical needs into platform capabilities and data models. What you bring: Must-haves: 7+ years in data engineering/architecture , including end-to-end ownership of a production data platform or warehouse. Proven experience consolidating data from multiple heterogeneous source systems into one analytical platform. Deep Azure data ecosystem expertise: Azure SQL, Synapse and/or Microsoft Fabric, Azure Data Factory or equivalent pipeline tooling. Data modeling across layers: dimensional (Kimball) for serving, plus an integration-layer methodology (medallion/lakehouse or Data Vault 2.0), and canonical/master data modeling. Hands-on Power BI : semantic models, DAX, deployment pipelines. Experience with multi-region or multi-country data platforms: data residency, GDPR, cross-border transfer constraints. Experience designing data contracts/exports from distributed or microservice-based systems. Ability to make and document architecture decisions (ADRs) and defend platform choices with trade-off analysis. Nice-to-haves: Microsoft Fabric migration experience (Synapse/SQL DW → Fabric). Master data management tooling or frameworks in practice. Legacy-to-SaaS data migration experience (mapping, cleansing, validation at scale). CI/CD for data (dbt, database projects, deployment pipelines in Azure DevOps). Healthcare or regulated-industry data experience (medical device or patient data a plus). What Success Looks Like (first 12 months): Target data platform strategy decided, documented (ADR), and roadmap approved - including the multi-region/residency approach. Manage data consolidated into a governed reporting layer feeding Power BI with agreed SLAs on freshness and quality. Cross-product consolidation architecture designed and validated with at least one additional product ingested. Canonical model and master-data rules defined for the first shared entities. Data contracts established with core domains; ingestion governed and observable. What's in it for you: Long-term engagement in a stable, growing SaaS company Remote-first and async-friendly with flat organizational structure High bar for engineering and product quality A team that values depth over hype: production quality over flashy prototypes A culture that values personal growth as much as business outcomes A global team that spans Denmark, Ukraine, UK, Poland, Canada, Australia, USA, and more. Feels like it’s a perfect match to you? We look forward to your application! (please submit your English CV) Auditdata is an equal opportunity employer that is committed to create diverse work environment free of discrimination and harassment. We make recruiting decisions based on your experience and skills.