MUST HAVE Mandatory Skills for each technology (All MUST)
Hands on experience with Microsoft Purview Data Catalog
Hands on experience with Microsoft Fabric (OneLake, Lakehouse/Warehouse)
Must have experience with Data Quality (DQ) & data profiling
Must have experience working with ontology structures and build relationship graphs

1. Objective
Establish a connected, enterprise-grade data Catalog and governance framework to support Symphony data sources, enabling end-to-end data product development, discoverability, data quality, lineage, and AI-driven operations using Microsoft Fabric and Microsoft Purview.

2 - Scope of Work
2.1 Data Catalog Development
Scan and onboard prioritized Symphony data sources into Microsoft Purview Data Catalog
Curate catalog assets by:
Updating business definitions
Maintaining and extending the business glossary
Aligning metadata for both existing and current Symphony datasets

2.2 Data Product Enablement
Design and develop end-to-end data products for Symphony datasets
Build and manage data storage using Microsoft Fabric (OneLake, Lakehouse/Warehouse)
Publish certified data products and associated metrics metadata for front-end consumption
Ensure alignment with governance standards and domain ownership

2.3 Data Modeling & Semantic Layer
Design and implement data models and entity relationships for catalog assets
Develop semantic models to support catalog output consumption
Standardize dimensions (e.g., Brand, Country) and metrics definitions

2.4 Ontology & Graph Enablement
Leverage entity models to define ontology structures
Enable ontology within Fabric and build relationship graphs to support data quality use cases across Symphony data sources




Support connected insights through relationship-aware data modeling

2.5 Data Quality & Profiling
Enable data profiling across Symphony datasets
Extend existing Data Quality (DQ) framework to cover new data sources
Publish DQ reports and dashboards
Implement DQ data agents for automated monitoring and issue detection

2.6 Data Lineage & Governance
Enable end-to-end data lineage across all Symphony data sources
Ensure traceability from source to consumption layer
Implement governance policies including:
Data classification
Ownership and stewardship
Access controls and compliance alignment

2.7 AI-Driven Capabilities
Design and develop AI agents to support:
Data quality monitoring
Metadata curation and recommendations
Data discovery and query assistance
Leverage AI capabilities within Fabric and Purview to automate and enhance operations

3. Deliverables
Connected Data Catalog with curated metadata and glossary
Certified Data Products and published metrics
Data Models and Semantic Layer for Symphony datasets
Ontology and Relationship Graphs enabled
Data Quality Framework Extension with reports and AI agents
Data Lineage Implementation across all relevant pipelines
AI Agents supporting governance and operations

4. Success Criteria
All prioritized Symphony data sources are cataloged and governed
Certified data products are available for business consumption
Data quality coverage and monitoring are established at scale
End-to-end lineage and traceability are enabled
AI-driven capabilities improve productivity and data trust

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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