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About the role
Role Overview: We are looking for an experienced Data Platform Architect to design and implement a scalable, end-to-end data platform using Microsoft Fabric. The role spans architecture, data engineering, modelling, analytics enablement, and integration with advanced data practices such as Medallion Architecture and AI/ML readiness. Key Responsibilities: - Architecture & Design: Define end-to-end architecture for a unified data platform using Microsoft Fabric. Implement Medallion Architecture (Bronze, Silver, Gold layers) and enforce data governance and security standards. - Data Engineering & Integration: Build batch and real-time data pipelines using Data Factory and Dataflow Gen2. Integrate and transform data into Lakehouse/Data Warehouse environments. - Data Modelling: Design star and snowflake schemas using dimensional (Kimball) and Lakehouse modelling techniques. - Analytics & Semantic Layer: Develop and optimize semantic models (Power BI datasets) to support self-service BI and reporting needs. - Performance Optimization: Tune pipelines, storage, and query performance for large-scale datasets (billions of records) using partitioning and cost optimization strategies. - Collaboration & Leadership: Translate business requirements into technical solutions while mentoring data engineers and BI developers on best practices and DataOps CI/CD workflows. Required Skills & Experience: - 10+ years of total experience in data/solution architecture. - 23 years of active, hands-on experience delivering Microsoft Fabric projects. - Solid expertise in Lakehouse, Data Warehouse, Data Factory, and Dataflow Gen2. - Solid programming skills in SQL and Spark/PySpark for distributed data processing. - In-depth understanding of data modelling (star/snowflake, Medallion Architecture, Data Vault). - Familiarity with Power BI datasets, data governance, and security compliance. - Experience with CI/CD and DataOps in data engineering pipelines. Good to Have: - Exposure to the broader Azure ecosystem (ADF, Synapse, ADLS). - Experience with open table formats (Delta Lake, Parquet). - ERP/CRM integration experience and awareness of embedding ML workflows within Fabric. .
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