Data Architect

Role Description

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.

Qualifications

• 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.

Requirements

• 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).

Benefits

• 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.

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.