Retail Data Architect | Remote | Contract

Amaze Systems Inc; Deutschland; Remote; EUR 65.000 - 90.000; Vollzeit

Zusammenfassung

Amaze Systems Inc. in Germany seeks a data modeling specialist to design and maintain enterprise data models across domains, including canonical and dimensional models.

You will use Erwin Data Modeler for forward and reverse engineering, perform data profiling, define quality rules and governance, and collaborate with MDM and data engineering teams to ensure compliant architectures.

Qualifikationen

• Experience building enterprise data models, canonical and dimensional models.
• Proficient with Erwin Data Modeler for modeling tasks.
• Ability to profile data and analyze source systems to understand data structures and rules.
• Define data quality rules, CDEs, standards, and validation requirements.
• Establish end-to-end data lineage with mappings and transformation logic.
• Define and implement data governance frameworks, including ownership and policies.
• Collaborate with MDM teams on master domains such as Customer, Product, and Store/Location.
• Define golden records, survivorship rules, and reference data.
• Develop and maintain metadata across business, technical, and operational layers.
• Work with data engineers, business analysts, data stewards, governance teams, and architects.
• Perform impact analysis for changes to source systems, models, and integrations.
• Ensure data architecture aligns with security, privacy, and regulatory requirements.

Aufgaben

• Develop and maintain enterprise data models, subject-area models, dimensional models, and canonical data models.
• Use Erwin Data Modeler for modeling, reverse/forward engineering, and model management.
• Perform data profiling and source-system analysis to understand data structures and business rules.
• Define data quality rules, CDEs, data standards, and validation requirements.
• Establish end-to-end data lineage, including mappings and transformation logic.
• Define and implement data governance frameworks, including ownership and policies.
• Collaborate with MDM teams on master domains (Customer, Product, Supplier, Store/Location).
• Define golden records, match/merge rules, survivorship rules, hierarchies, and reference data.
• Develop and maintain business, technical, and operational metadata.
• Collaborate with data engineers, analysts, stewards, governance teams, and application architects.
• Perform impact analysis for changes to source systems, data models, integrations, and downstream consumers.
• Ensure data architecture aligns with security, privacy, and regulatory requirements.
• Support modernization initiatives involving Data Warehouse, Data Lake, Lakehouse, and cloud platforms.

Kenntnisse

Enterprise data modeling

Data governance

Data profiling

Source-system analysis

Impact analysis

Collaboration

Tools

Erwin Data Modeler

Jobbeschreibung

Design conceptual, logical, and physical data models for enterprise retail data platforms.

• Develop and maintain enterprise data models, subject-area models, dimensional models, and canonical data models.
• Use Erwin Data Modeler for data modeling, reverse engineering, forward engineering, and model management.
• Perform data profiling and source-system analysis to understand data structures, relationships, quality issues, and business rules.
• Define data quality rules, Critical Data Elements (CDEs), data standards, and validation requirements.
• Establish and maintain end-to-end data lineage, including source-to-target mappings and transformation logic.
• Define and implement data governance frameworks, including ownership, stewardship, policies, standards, and business glossaries.
• Work with Master Data Management (MDM) teams on Customer, Product, Supplier, Store/Location, and other master domains.
• Define golden records, match/merge rules, survivorship rules, hierarchies, and reference data.
• Develop and maintain business, technical, and operational metadata.
• Collaborate with data engineers, business analysts, data stewards, governance teams, and application architects.
• Perform impact analysis for changes to source systems, data models, integrations, and downstream consumers.
• Ensure data architecture aligns with enterprise architecture, security, privacy, and regulatory requirements.
• Support modernization initiatives involving Data Warehouse, Data Lake, Lakehouse, cloud platforms, and analytics environments.