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Job Title: Fabric Architect
EXL is looking for a Fabric Architect who is responsible for designing, implementing, and governing an enterprise-wide data fabric architecture leveraging Microsoft Fabric (or equivalent cloud data fabric solutions).This role focuses on building a unified, scalable, and secure data platform that integrates data ingestion, transformation, governance, analytics, and AI workloads across multiple business domains.
Responsibilities:
Define and implement end-to-end data fabric architecture using Microsoft Fabric components (Data Factory, Synapse, Power BI, OneLake, Lakehouse).
Design data ingestion, transformation, and orchestration frameworks supporting both batch and real-time data integration.
Develop metadata-driven ingestion, audit, balance, and control frameworks to ensure data consistency and traceability.
Architect semantic data models and analytical layers for enterprise-wide KPIs, reporting, and AI enablement.
Create data modeling standards and blueprints for dimensional, logical, and physical models (Star/Snowflake schemas).
Lead design and implementation of data pipelines and integration patterns using Python, SQL, Spark, and Fabric Data Factory.
Oversee data ingestion from structured, semi-structured, and unstructured sources into the Fabric Lakehouse or Warehouse.
Ensure data quality, lineage, and metadata management across all data domains.
Integrate Fabric platform with Azure and other cloud ecosystems for unified data access
Define and implement data governance policies, metadata management, and cataloging using Microsoft Purview or Fabric-native capabilities.
Ensure compliance with enterprise and regulatory standards (GDPR, HIPAA, SOC2, etc.).
Implement row-level and column-level security, encryption, and access control frameworks.
Establish data lifecycle management and retention strategies
Collaborate with business and analytics teams to define KPIs, semantic models, and reporting frameworks.
Enable self-service analytics through well-structured Power BI datasets and data marts.
Optimize query performance, data partitioning, and model efficiency for large-scale analytics
Lead and mentor technical teams on Fabric best practices, design patterns, and reusable components.
Required Qualifications:
10-12 years of overall experience in data architecting, design, and development of data warehouse systems (Cloud/on premises and Analytics) at enterprise scale.
·Must have implemented end to end platform modernization projects.
· Strong experience with Microsoft Fabric, Azure Synapse, Databricks or similar modern data platforms.
· Proven expertise in data modeling (ER/Studio, ERWin, dbt, Power BI Semantic Models), data integration, and data governance frameworks.
· Good knowledge of Azure DevOps, GitHub Actions, CI/CD Pipelines
· Strong collaboration, communication, and leadership skills in cross-functional environments.
· Must be hands on, deeply technical and exposure to latest features within data platform development, able to do both coding and guide group of junior/mid-level database engineers.
· Must have at least 5+ experience in managing technical team and leading them to deliver large scale solutions.
· Must have excellent communication skills (English) to interface with US clients directly and verify in proficient in all types of communication modes Listening, Reading, Writing and Speaking
· Must have strong experience in Performance Tuning / Optimization Initiatives using DB Profiler tools
· Must have strong experience in taking ownership in delivering other activities apart from Project deliverables like SoW writing, performance management, initiatives, offshore team management, recruitment etc.
· Experience in a variety of business verticals with preference to Insurance and banking.
· Ability to act independently to resolve issues, excellent communication (English) and interpersonal skills, strong critical analytic thinking.
· Ability to manage team a through the entire development life cycle and to manage time effectively.
Responsibilities:
Define and implement end-to-end data fabric architecture using Microsoft Fabric components (Data Factory, Synapse, Power BI, OneLake, Lakehouse).
Design data ingestion, transformation, and orchestration frameworks supporting both batch and real-time data integration.
Develop metadata-driven ingestion, audit, balance, and control frameworks to ensure data consistency and traceability.
Architect semantic data models and analytical layers for enterprise-wide KPIs, reporting, and AI enablement.
Create data modeling standards and blueprints for dimensional, logical, and physical models (Star/Snowflake schemas).
Lead design and implementation of data pipelines and integration patterns using Python, SQL, Spark, and Fabric Data Factory.
Oversee data ingestion from structured, semi-structured, and unstructured sources into the Fabric Lakehouse or Warehouse.
Ensure data quality, lineage, and metadata management across all data domains.
Integrate Fabric platform with Azure and other cloud ecosystems for unified data access
Define and implement data governance policies, metadata management, and cataloging using Microsoft Purview or Fabric-native capabilities.
Ensure compliance with enterprise and regulatory standards (GDPR, HIPAA, SOC2, etc.).
Implement row-level and column-level security, encryption, and access control frameworks.
Establish data lifecycle management and retention strategies
Collaborate with business and analytics teams to define KPIs, semantic models, and reporting frameworks.
Enable self-service analytics through well-structured Power BI datasets and data marts.
Optimize query performance, data partitioning, and model efficiency for large-scale analytics
Lead and mentor technical teams on Fabric best practices, design patterns, and reusable components.
10-12 years of overall experience in data architecting, design, and development of data warehouse systems (Cloud/on premises and Analytics) at enterprise scale.
· Must have implemented end to end platform modernization projects.
· Strong experience with Microsoft Fabric, Azure Synapse, Databricks or similar modern data platforms.
· Proven expertise in data modeling (ER/Studio, ERWin, dbt, Power BI Semantic Models), data integration, and data governance frameworks.
· Good knowledge of Azure DevOps, GitHub Actions, CI/CD Pipelines
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