Data Architect

O tym stanowisku

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…