Fabric Architect

Job Title

Responsibilities

Design end-to-end Microsoft Fabric architectures using One Lake, Lakehouse, Data Warehouse, pipelines, notebooks, and Power BI.

Define Bronze/Silver/Gold medallion architecture and enterprise standards for ingestion, transformation, storage, modelling, and consumption.

Establish One Lake, workspace, domain, naming, shortcut, and data-sharing standards.

Design scalable solutions for structured, semi-structured, and unstructured data.

Build enterprise Power BI semantic architectures using dimensional modelling, star schemas, shared dimensions, governed measures, DAX, and calculation groups.

Determine the appropriate use of Direct Lake, Import, Direct Query, and composite models based on performance, scale, freshness, security, and business requirements.

Design batch, near-real-time, and event-driven data integration patterns using Data Factory, Dataflows Gen2, Spark, SQL, notebooks, and APIs.

Optimize Fabric capacity, Delta tables, SQL workloads, pipelines, semantic models, and reports for performance and cost.

Define enterprise security using Entra , RBAC, RLS, OLS, managed identities, and data classification.

Establish governance, lineage, metadata, retention, auditing, compliance, and data-quality standards.

Create reusable architecture patterns, templates, reference implementations, and technical standards.

Lead architecture/design reviews, technical assessments, and proofs of concept.

Define source control, testing, CI/CD, deployment, and environment-management practices.

Troubleshoot complex performance, security, capacity, and data-reliability issues.

Maintain architecture diagrams, data flows, standards, and design documentation.

Requirements

8+ years of experience in data architecture, data engineering, business intelligence, analytics architecture, or enterprise data-platform delivery.

Strong hands-on experience designing and implementing production solutions using Microsoft Fabric;
Microsoft Fabric certification (DP-600 and/or DP-700) is preferred.

Relevant Power BI, Azure data, or architecture certification.

Deep understanding of One Lake, Fabric Lakehouse, Fabric Data Warehouse, Data Factory, notebooks, pipelines, semantic models, and Power BI.

Strong experience with medallion architecture, data-lake architecture, Delta Lake, Parquet, and scalable data-processing patterns.

Expertise in dimensional modelling, star and snowflake schemas, slowly changing dimensions, shared dimensions, metrics, and enterprise semantic modelling.

Strong Power BI semantic-model development experience, including DAX, Power Query, calculation groups, relationships, aggregations, incremental refresh, and performance optimisation.

Experience selecting and implementing Direct Lake, Import, Direct Query, and composite storage modes.

Advanced SQL skills and strong working knowledge of Python or PySpark.

Experience integrating relational databases, files, APIs, cloud services, external data sources, and streaming or event-based sources.

Strong knowledge of data security, governance, lineage, classification, privacy, and access-control principles.

Experience designing data-quality, reconciliation, observability, monitoring, and exception-management frameworks.

Strong understanding of Fabric capacity management, workload monitoring, query optimisation, scalability, resilience, and cost management.

Experience with Git-based development, automated testing, CI/CD, deployment pipelines, and environment-management practices.

Ability to convert complex business requirements into clear architecture, models, technical specifications, and delivery plans.

Strong analytical, troubleshooting, documentation, consulting, and stakeholder-management skills.

Ability to provide technical leadership across multiple teams without losing hands-on involvement.

Bachelor's degree in Computer Science, Data Engineering, Information Systems, or an equivalent discipline.

Nice to have

Experience working with investment management, asset management, fixed income, financial products, risk, compliance, or distribution datasets.

Experience with Microsoft Purview, Azure Data Lake Storage, Azure Data Factory, Azure Synapse Analytics, Azure Key Vault, and…