1. MDM Architect

Experience & Qualifications

·       12+ years of experience in Data Architecture, Enterprise Data Management, and Master Data Management (MDM).

·       7+ years of experience in MDM architecture, solution design, or implementation.

·       10+ years experience in T-SQL 

·       Proven experience designing and implementing enterprise-scale data platforms and MDM solutions.

·       Experience with at least one major MDM platform such as Informatica MDM, Reltio, SAP MDG, Semarchy, Profisee, or Ataccama.

·       Experience working across multiple master-data domains such as Customer, Product, Supplier, Employee, Location, and Finance.

·       Strong understanding of Data Governance, Data Quality, Data Stewardship, and Metadata Management.

·       Experience leading architecture discussions with business stakeholders, data owners, technical teams, and enterprise architects.

·       Strong experience in developing architecture standards, design principles, reusable patterns, and technical roadmaps.

Key Responsibilities

1. MDM Strategy & Architecture

·       Define the enterprise MDM strategy, principles, standards, architecture, and implementation roadmap.

·       Design end-to-end MDM architecture using Snowflake as the enterprise data platform.

·       Define current-state, transitional, and target-state MDM architectures.

·       Design MDM capabilities covering:

o   Master data ingestion

o   Data standardization

o   Data quality

o   Matching and deduplication

o   Golden record creation

o   Survivorship

o   Master data distribution

o   Data governance

·       Define reusable MDM architecture, data integration, and implementation patterns.

·       Define master entities, attributes, relationships, and hierarchies.

·       Develop conceptual, logical, and physical data models.

·       Define systems of record and authoritative data sources.

·       Define canonical master-data structures.

·       Establish cross-domain relationships and dependencies.

2. Data Quality & Mastering

·       Define and implement an enterprise MDM data quality strategy and framework.

·       Lead source-system data profiling and data quality assessments.

·       Define data quality rules and validation frameworks for Snowflake-based master-data pipelines.

·       Identify duplicate, incomplete, inconsistent, and conflicting master-data records.

·       Design matching, deduplication, and merging strategies and algorithms.

·       Define survivorship rules and source-priority frameworks.

·       Establish attribute-level source precedence and conflict-resolution rules.

·       Design and maintain Golden Record / Single Source of Truth solutions.

·       Establish data quality KPIs, scorecards, thresholds, and monitoring mechanisms.

·       Define data remediation and data cleansing strategies.

3. Data Governance

·       Define and implement the MDM Data Governance Framework.

·       Establish Data Owner, Data Steward, Data Custodian, and Governance Council responsibilities.

·       Define MDM governance RACI and operating model.

·       Establish master-data policies, standards, procedures, and controls.

·       Define data ownership and accountability across master-data domains.

·       Establish data quality KPIs, SLAs, and governance metrics.

·       Define metadata, business glossary, data lineage, and data classification requirements.

·       Establish processes for master-data creation, modification, approval, remediation, and retirement.

·       Integrate MDM governance with enterprise data governance platforms such as Microsoft Purview, where applicable.

4. Security & Compliance

·       Define the MDM security and access-control architecture.

·       Establish role-based access controls for master-data domains and users.

·       Define data security, privacy, masking, encryption, and audit requirements.

·       Ensure appropriate protection of sensitive and confidential master data.

·       Define data retention, archival, and deletion requirements.

·       Ensure MDM architecture complies with enterprise security and regulatory requirements.

·       Work with security and compliance teams to address data privacy, auditability, and regulatory controls.

1. MDM Architect

Experience & Qualifications

·       12+ years of experience in Data Architecture, Enterprise Data Management, and Master Data Management (MDM).

·       7+ years of experience in MDM architecture, solution design, or implementation.

·       10+ years experience in T-SQL 

·       Proven experience designing and implementing enterprise-scale data platforms and MDM solutions.

·       Experience with at least one major MDM platform such as Informatica MDM, Reltio, SAP MDG, Semarchy, Profisee, or Ataccama.

·       Experience working across multiple master-data domains such as Customer, Product, Supplier, Employee, Location, and Finance.

·       Strong understanding of Data Governance, Data Quality, Data Stewardship, and Metadata Management.

·       Experience leading architecture discussions with business stakeholders, data owners, technical teams, and enterprise architects.

·       Strong experience in developing architecture standards, design principles, reusable patterns, and technical roadmaps.

Key Responsibilities

1. MDM Strategy & Architecture

·       Define the enterprise MDM strategy, principles, standards, architecture, and implementation roadmap.

·       Design end-to-end MDM architecture using Snowflake as the enterprise data platform.

·       Define current-state, transitional, and target-state MDM architectures.

·       Design MDM capabilities covering:

o   Master data ingestion

o   Data standardization

o   Data quality

o   Matching and deduplication

o   Golden record creation

o   Survivorship

o   Master data distribution

o   Data governance

·       Define reusable MDM architecture, data integration, and implementation patterns.

·       Define master entities, attributes, relationships, and hierarchies.

·       Develop conceptual, logical, and physical data models.

·       Define systems of record and authoritative data sources.

·       Define canonical master-data structures.

·       Establish cross-domain relationships and dependencies.

2. Data Quality & Mastering

·       Define and implement an enterprise MDM data quality strategy and framework.

·       Lead source-system data profiling and data quality assessments.

·       Define data quality rules and validation frameworks for Snowflake-based master-data pipelines.

·       Identify duplicate, incomplete, inconsistent, and conflicting master-data records.

·       Design matching, deduplication, and merging strategies and algorithms.

·       Define survivorship rules and source-priority frameworks.

·       Establish attribute-level source precedence and conflict-resolution rules.

·       Design and maintain Golden Record / Single Source of Truth solutions.

·       Establish data quality KPIs, scorecards, thresholds, and monitoring mechanisms.

·       Define data remediation and data cleansing strategies.

3. Data Governance

·       Define and implement the MDM Data Governance Framework.

·       Establish Data Owner, Data Steward, Data Custodian, and Governance Council responsibilities.

·       Define MDM governance RACI and operating model.

·       Establish master-data policies, standards, procedures, and controls.

·       Define data ownership and accountability across master-data domains.

·       Establish data quality KPIs, SLAs, and governance metrics.

·       Define metadata, business glossary, data lineage, and data classification requirements.

·       Establish processes for master-data creation, modification, approval, remediation, and retirement.

·       Integrate MDM governance with enterprise data governance platforms such as Microsoft Purview, where applicable.

4. Security & Compliance

·       Define the MDM security and access-control architecture.

·       Establish role-based access controls for master-data domains and users.

·       Define data security, privacy, masking, encryption, and audit requirements.

·       Ensure appropriate protection of sensitive and confidential master data.

·       Define data retention, archival, and deletion requirements.

·       Ensure MDM architecture complies with enterprise security and regulatory requirements.

·       Work with security and compliance teams to address data privacy, auditability, and regulatory controls.