Data Architect Expert is responsible for designing, governing, and optimizing enterprise data architecture to support business strategy, digital transformation, analytics, artificial intelligence (AI), and regulatory compliance. This role provides technical leadership in data modeling, data integration, master data management, data governance, cloud data platforms, and enterprise data solutions.
The successful candidate will define data architecture standards, ensure data consistency and quality, and establish scalable data ecosystems that enable trusted, accessible, and actionable enterprise data.
Key Responsibilities
1. Enterprise Data Architecture
- Design and maintain enterprise-wide data architecture frameworks, principles, and standards.
- Develop conceptual, logical, and physical data models across business domains.
- Define data architecture roadmaps aligned with organizational objectives.
- Establish best practices for data lifecycle management and data integration.
- Evaluate emerging technologies and recommend architecture improvements.
2. Data Platform & Solution Design
- Architect modern data platforms including:
- Data Warehouse
- Data Lake
- Lakehouse Architecture
- Data Mesh
- Data Fabric
- Design scalable, secure, and high-performance data solutions.
- Lead cloud data architecture initiatives on AWS, Azure, or Google Cloud.
- Develop data storage, processing, and access strategies.
3. Data Integration & Engineering
- Design enterprise data integration frameworks.
- Define standards for ETL/ELT pipelines and data ingestion processes.
- Ensure reliable movement of data across internal and external systems.
- Collaborate with Data Engineers to optimize performance and scalability.
- Support real-time and batch data processing architectures.
4. Data Governance & Quality
- Establish enterprise data governance policies and standards.
- Define metadata management and data catalog strategies.
- Implement data quality, lineage, and stewardship frameworks.
- Ensure compliance with security, privacy, and regulatory requirements.
- Promote enterprise-wide adoption of data governance practices.
5. Analytics & AI Enablement
- Design architectures supporting:
- Business Intelligence (BI)
- Advanced Analytics
- Machine Learning
- Artificial Intelligence
- Enable self-service analytics environments.
- Support development of trusted datasets for analytical use cases.
- Optimize data accessibility for business and technical stakeholders.
6. Stakeholder Management
- Partner with business leaders to understand data requirements.
- Translate business objectives into architecture solutions.
- Provide technical leadership and guidance to data teams.
- Facilitate architecture reviews and governance committees.
- Communicate complex technical concepts to non-technical audiences.
7. Security & Compliance
- Design secure data architectures following industry standards.
- Implement data classification and protection mechanisms.
- Ensure compliance with:
- GDPR
- PDPA
- HIPAA (where applicable)
- Industry regulatory requirements
- Conduct architecture risk assessments and mitigation planning.
Required Qualifications
Education
- Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or related field.
- Master's degree is preferred.
Experience
- 8+ years of experience in Data Management, Data Engineering, or Enterprise Architecture.
- 5+ years of experience in data architecture leadership roles.
- Proven experience designing enterprise-scale data platforms.
- Experience implementing cloud-native data architectures.
- Experience with large-scale data transformation initiatives.
Technical Skills
Data Architecture
- Enterprise Data Architecture
- Data Modeling (Conceptual, Logical, Physical)
- Master Data Management (MDM)
- Metadata Management
- Data Governance
- Data Quality Frameworks