Data Architect

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Auditdata

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 1992

⚕️ Healthcare Insurance

📡 Telecommunications

💰 Venture Round on 2016-07

Healthcare Insurance • Software • Telecommunications

Auditdata is a cloud-based, data-driven practice management software company specializing in solutions for audiology practices. Their offerings include practice management software that optimizes workflows, integrated audiological testing equipment, and screening tools for improved patient care. Auditdata's technology enhances the patient experience at every stage from screening to fitting and aftercare, ensuring efficiency and high-quality service delivery.

📋 Description

• 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. • 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). • 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. • 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. • 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. • Work with business stakeholders across products and countries to translate analytical needs into platform capabilities and data models.

🎯 Requirements

• 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.

🏖️ 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.