Data Platform Architect (Microsoft Fabric)

Data Platform Architect (Microsoft Fabric)1 Data Platform Architect (Microsoft Fabric) **Experience: 10+ years overall, with 2–3 years hands-on experience in Microsoft Fabric (project experience required) **Role Type: Contractor **Location: Pune ## 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 ###

1. Architecture & Design

• Define end-to-end architecture for a unified data platform using Microsoft Fabric.
• Design scalable, secure, and high-performance solutions.
• Establish integration strategies across enterprise systems (ERP, CRM, SaaS).
• Enforce data governance, security, and compliance standards.
• Implement Medallion Architecture (Bronze, Silver, Gold layers) for structured data transformation and quality. ###

1. Data Engineering & Integration

• Build data pipelines using Data Factory and Dataflow Gen2.
• Develop ETL/ELT processes (incremental and full loads).
• Integrate and transform data into Lakehouse/Data Warehouse.
• Architect pipelines supporting both batch and real-time processing.
• Apply DataOps practices and CI/CD for pipeline automation. ###

1. Data Modelling

• Design star and snowflake schemas.
• Define data standards, naming conventions, and best practices.
• Ensure data quality, consistency, and integrity.
• Apply dimensional (Kimball) and Lakehouse modelling techniques. ###

1. Analytics & Semantic Layer

• Develop semantic models (Power BI datasets).
• Optimize models for reporting and analytics.
• Support basic reporting and visualization needs.
• Enable self-service BI through well-structured semantic layers. ###

1. Performance Optimization

• Tune pipelines, storage, and query performance.
• Apply partitioning, indexing, and cost optimization strategies.
• Handle large-scale datasets (billions of records) efficiently. ###

1. Collaboration & Leadership

• Translate business requirements into technical solutions.
• Guide data engineers and BI developers.
• Align architecture, engineering, and analytics teams.
• Mentor teams and enforce best practices, coding standards, and design patterns. ###

1. Advanced Capabilities

• Establish metadata management, lineage tracking, and cataloging frameworks.
• Provide architectural guidance for AI/ML integration (feature stores, model pipelines).
• Ensure compliance with regulatory standards (GDPR, HIPAA, etc.). ## Required Skills - 10+ years in data/solution architecture. - 2–3 years of hands-on Microsoft Fabric experience (must have delivered Fabric projects).
• Expertise in Lakehouse, Data Warehouse, Data Factory, Dataflow Gen2.
• Strong SQL and ETL/ELT development skills.
• Data modelling expertise (star/snowflake schemas, Data Vault, Medallion).
• Experience with large-scale data and performance tuning.
• Knowledge of Power BI (datasets, relationships, basic reporting).
• Understanding of data governance, security, and quality.
• Strong knowledge of Spark/PySpark for distributed data processing.
• Experience with CI/CD and DataOps in data engineering. ## Good to Have
• Broader Azure ecosystem (ADF, Synapse, ADLS).
• Python / Spark / PySpark advanced use cases.
• ERP/CRM integrations.
• Power BI performance optimization.
• Familiarity with open table formats (Delta Lake, Parquet).
• Awareness of integrating ML workflows with Fabric. ## Success Criteria
• Scalable and well-architected Fabric platform.
• Reliable and efficient data pipelines (batch + real-time).
• High-quality, structured data models with Medallion layering.
• Seamless data integration across enterprise systems.
• AI/ML-ready datasets and workflows.
• Fast and optimized reporting with self-service BI enablement.