Data Platform Architect

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.  

### 2) 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.  

### 3) 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. 

### 4) 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.  

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

### 6) 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.  

### 7) 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.

Experience Level

Senior Level