Us And Help Shape
DataArchitect,MasterDataManagement
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Architect, Master Data Management at Us And Help Shape. Skills: Data Architecture, Master Data Management, Enterprise data flows, Data governance. Define enterprise MDM architecture strategy. Design data architecture patterns”
What They're Looking For.
Must Have
10-14 years of Experience, Data Architecture experience, Master Data Management experience, Enterprise-scale systems experience, Global systems experience, Strategic transformation programs experience, Conceptual data modeling, Logical data modeling, Physical data modeling, Integration patterns experience, API integration experience, ETL/ELT integration experience, Streaming integration experience, Event-driven architecture experience, Middleware orchestration experience, Data architecture diagrams, Data flow diagrams, Domain models, System interaction views, Architecture decision records, Stakeholder management skills, Facilitation skills
Nice to Have
PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, dbt Certified
What You'll Do.
Define enterprise MDM architecture strategy
Design data architecture patterns
Translate business architecture
Translate business capabilities
Translate business processes
Develop conceptual data models
Develop logical data models
Develop physical data models
Support MDM initiatives
Support enterprise data initiatives
Establish architecture principles
Establish architecture standards
Establish best practices for master data
Establish best practices for reference data
Establish best practices for metadata
Establish best practices for data quality
Establish best practices for data lifecycle management
Collaborate with business teams
Collaborate with product owners
Collaborate with enterprise architects
Collaborate with application teams
Collaborate with data engineering teams
Collaborate with governance partners
Define critical data entities
Define business rules
Define matching logic
Define survivorship rules
Define stewardship processes
Define consumption patterns
Architect end-to-end data flows
Document end-to-end data flows
Ensure data consistency
Ensure data traceability
Design integration patterns for master data synchronization
Design integration patterns for event-based distribution
Design integration patterns for API-driven access
Design integration patterns for batch pipelines
Design integration patterns for real-time data exchange
Ensure alignment between MDM solutions
Ensure alignment with enterprise integration platforms
Ensure alignment with analytics platforms
Ensure alignment with operational systems
Ensure alignment with modern cloud data platforms
Embed data governance principles
Define data ownership
Define data stewardship
Define data classification
Define compliance requirements
Define frameworks for data quality
Support data profiling
Support data standardization
Support data deduplication
Support data enrichment
Support data monitoring
Support issue remediation
Drive adoption of metadata management
Drive adoption of lineage capabilities
Drive adoption of catalog capabilities
Improve transparency in enterprise data assets
Improve trust in enterprise data assets
Evaluate business requirements
Evaluate technical requirements
Recommend target-state architecture solutions
Contribute to architecture roadmaps
Contribute to reference architectures
Contribute to capability assessments
Contribute to investment planning
Review solution designs
Guide implementation teams
Ensure adherence to architectural standards
Ensure long-term maintainability
Support strategic programs
Identify opportunities to simplify data landscape
Identify opportunities to reduce duplication
Identify opportunities to improve interoperability
Identify opportunities to increase data reuse
Stay current on evolving technologies
Stay current on architecture patterns
Stay current on MDM trends
Stay current on data management trends
Contribute to architecture community of practice
How You'll Work.
Team & Collaboration
Partner with business stakeholders; Partner with enterprise architects; Partner with product teams; Partner with engineering teams; Partner with technology organizations; Collaborate with business teams; Collaborate with product owners; Collaborate with enterprise architects; Collaborate with application teams; Collaborate with data engineering teams; Collaborate with governance partners; Work across global teams; Influence decisions across business; Influence decisions across product; Influence decisions across engineering; Influence decisions across governance; Influence decisions across architecture
Communication Scope
Communication skills; Stakeholder management; Facilitation skills
Process & Methodology
Roadmap planning
Full Job Description
**Role Summary** We are seeking a **Data Architect, Master Data Management (MDM)** to define, shape, and implement enterprise-wide data architecture with a strong focus on **master data domains, governance, integration, and enterprise data flows**. This role will partner closely with business stakeholders, enterprise architects, product teams, engineering teams, and other technology organizations to ensure business architecture is translated into **scalable, governed, and future-ready data architecture solutions**. This is a high-impact role for someone who combines **strategic thinking with hands-on architectural leadership**. You will help design and govern how critical business data is structured, integrated, managed, and consumed across the enterprise, enabling trusted and reusable data foundations across global strategic programs. ## _About the Role_ * Define and evolve the **enterprise MDM architecture strategy** in alignment with business priorities, enterprise architecture standards, and digital transformation goals. * Design scalable data architecture patterns for managing core and master data across domains such as **customer, product, vendor, reference, organizational, and other critical enterprise entities**. * Translate **business architecture, capabilities, and processes** into data architecture, domain models, and end-to-end enterprise data flows. * Develop **conceptual, logical, and physical data models** to support MDM and broader enterprise data initiatives. * Establish architecture principles, standards, and best practices for: * Master data * Reference data * Metadata * Data quality * Data lifecycle management * Collaborate with business teams, product owners, enterprise architects, application teams, data engineering teams, and governance partners on **global strategic initiatives**. * Partner with stakeholders to define critical data entities, business rules, matching and merging logic, survivorship rules, stewardship processes, and consumption
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