Data Management Solution Architect

Role Summary: We are seeking a strong MDM-centric Data Management Architect to solution design enterprise-grade Master Data Management solutions while contributing to broader Data Governance, Data Quality, and Modern Data Platform initiatives. This role is expected to anchor MDM design and implementation, support data governance, quality, and security integration, contribute to modern data architectures (Fabric/Mesh), and gradually step into solutioning and client-facing roles.

Core Responsibilities:
- Master Data Management: Design and implement multi-domain MDM solutions (Customer, Product, Vendor, Reference Data) & PIM. Define Golden Record strategy (match, merge, survivorship, hierarchies). Build data models and entity relationships. Implement data onboarding (batch + real-time), match rules, workflows, stewardship processes, and hierarchy management. Integrate MDM with source systems (ERP, CRM, APIs) and downstream analytics platforms.
- MDM + Data Quality Convergence: Implement pre- and post-MDM DQ frameworks (profiling, standardization, validation). Design DQ rules library aligned with MDM entities. Support data cleansing, enrichment, and continuous DQ monitoring/KPI reporting.
- Data Governance Enablement: Align MDM with enterprise data governance policies. Support data catalog integration, business glossary & metadata mapping, stewardship workflows, and ensure data ownership, lineage, and lifecycle visibility.
- Data Security & Compliance: Implement access control (RBAC), masking, sensitive data handling, and compliance for PII/reference data domains. Support audit trails and data access monitoring.
- Modern Data Platform Integration: Integrate MDM with modern data platforms (Lakehouse/Warehouse). Work with Databricks/Snowflake data pipelines, ingestion, transformation, and API frameworks. Enable MDM as a service layer (API-first/event-driven) and support Data Fabric integration.
- Data Mesh & Data Product Alignment: Support adoption of Data Mesh principles, domain-aligned master data ownership, and data-as-a-product mindset. Collaborate with domain teams for data product publishing.
- Data Observability & Monitoring: Implement DQ & pipeline monitoring (freshness, completeness, failures). Enable issue detection, root cause analysis, remediation workflows, automated alerts, and dashboards.
- Solutioning & Client Interaction: Participate in solution design discussions, effort estimation, technical proposals, client workshops, requirement discovery, POCs, demos, and accelerators. Execution-heavy with growing consulting exposure.