Designs and governs enterprise-scale Azure and Microsoft Fabric data platforms for finance, accounting, and other domains. The role owns data architecture strategy, lakehouse and warehouse design, ingestion, governance, lineage, quality, security, BI standards, lifecycle management, and polyglot database strategies. It integrates ERP and business systems, enables AI-ready architectures, and provides technical roadmaps and stakeholder guidance. The position requires deep Azure, Fabric, data modeling, governance, SQL/ Python/Spark, and enterprise database expertise, plus finance or accounting domain experience.
This is a remote position.
Role Overview
Integrella is seeking an experienced Data Architect to design and govern modern, enterprise-scale data platforms for finance, accounting and multiple domains. This role requires deep expertise across the Microsoft Azure data stack and Microsoft Fabric, with a focus on building well-modelled, well-governed, and audit-ready data foundations for financial and regulatory use cases.
You will define enterprise data architecture, data lake and data warehouse design, and establish governance, master data, and BI standards that turn complex ERP, Payroll and financial data into trusted, decision-ready assets for global clients.
Key Responsibilities
- Define and own the enterprise data architecture strategy, standards, principles, and technology roadmap across multiple business domains.
- Architect scalable, secure, and cloud-native data platforms supporting operational reporting, advanced analytics, AI, and machine learning workloads.
- Design and oversee enterprise Data Lake, Lakehouse, and Data Warehouse solutions using Azure Data Factory, Azure Data Lake Storage (ADLS Gen2), Azure Databricks, Microsoft Fabric, Synapse Analytics, or equivalent cloud data platforms.
- Lead the adoption and architecture of Microsoft Fabric, including One Lake, Lakehouse, Data Warehouse, Data Pipelines, Direct Lake, Real-Time Intelligence, and Semantic Models.
- Define data ingestion strategies supporting batch, streaming, event-driven, and real-time data integration using Azure Event Hubs, Service Bus, Kafka, and modern messaging platforms.
- Design and implement modern data architectures, including Medallion (Bronze, Silver, Gold), Delta Lake, Data Vault 2.0, dimensional modelling, and canonical data models.
- Establish enterprise metadata management, data governance, lineage, classification, and data cataloguing using Microsoft Purview or equivalent governance platforms.
- Architect enterprise data integration for ERP, CRM, HR, Finance, and operational systems, including Workday, SAP, Oracle, Dynamics 365, Salesforce, and other business applications.
- Develop enterprise data quality, validation, reconciliation, and observability frameworks to ensure trusted, auditable, and high-quality data.
- Define enterprise standards for Power BI Semantic Models, Direct Lake, Row-Level Security (RLS), data sharing, and Business Intelligence governance.
- Design secure, scalable, and resilient data platforms with a strong focus on security, privacy, performance, disaster recovery, and cost optimisation.
- Collaborate with Integration Architects to establish API-first and event-driven data integration patterns across enterprise platforms.
- Enable AI-ready data platforms by designing architectures that support Azure AI, Azure OpenAI, Microsoft Copilot, Azure AI Search, vector databases, and Retrieval-Augmented Generation (RAG) solutions.
- Define enterprise data lifecycle management, including ingestion, transformation, storage, retention, archival, and regulatory compliance.
- Evaluate emerging technologies and provide strategic recommendations to evolve the organisation's modern data platform capabilities.
- Define enterprise data storage strategies across relational (SQL), NoSQL, graph, time-series, and object storage technologies, ensuring the appropriate database platform is selected based on scalability, performance, consistency, and business requirements.
- Define data partitioning, indexing, sharding, replication, caching, and disaster recovery strategies to optimise platform performance, availability, and scalability.
- Establish enterprise standards for database security, encryption, backup and recovery, data retention, and performance monitoring across SQL and NoSQL platforms.
- Provide architectural guidance on polyglot persistence, ensuring the most appropriate data storage technology is selected for each business capability and workload.
Technical Skills Required
- 8+ years of experience in data architecture, data engineering, or enterprise data roles, with at least 3 years focused on finance, tax, or accounting domains
- Deep hands-on expertise with the Microsoft Azure data stack: Azure Data Factory, Azure Data Lake Storage Gen2, Azure Databricks (Delta Live Tables, Unity Catalog), and Synapse Analytics
- Strong proficiency in Microsoft Fabric: Lakehouse, Data Warehouse, Pipelines, Direct Lake, and OneLake architecture
- Experience with Microsoft Purview for data governance, cataloguing, lineage, and policy management
- Proficiency in SQL, Python, and/or Spark for data modelling, transformation, and quality validation
- Strong knowledge of dimensional modelling, data vault, and canonical data model design patterns
- Experience with Delta Lake / Medallion Architecture (Bronze-Silver-Gold) for financial data
- Familiarity with ERP data structures – particularly Workday, SAP, or Oracle Finance – and their integration into data platforms
- Architect and govern enterprise SQL and NoSQL database solutions, including Microsoft SQL Server, Azure SQL Database, PostgreSQL, MySQL, Oracle, MongoDB, Apache Cassandra, Couchbase, Azure Cosmos DB, Redis, and other modern cloud-native data platforms.
- Familiarity with Azure DevOps, CI/CD pipelines, and infrastructure-as-code for data platform deployments
Requirements
Technical Skills – Advantageous
Exposure to e-Invoicing standards and tax authority data exchange formats (e.g. SAF-T, PEPPOL, e-Fattura)
What We’re Looking For
- Proven ability to define and communicate enterprise data architecture vision, standards, and roadmaps
- Strong understanding of data modelling, governance, and data platform design principles
- Experience working in Agile/Scrum environments and distributed delivery teams
- Ability to communicate effectively with both technical and non-technical stakeholders
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