Key Responsibilities
Data Architecture & Design
- Define and maintain enterprise-wide data architecture blueprints (logical, physical, and conceptual models)
- Design scalable data platforms including data lakes, data warehouses, lakehouses, and streaming architectures
- Establish standards for data modeling, integration, storage, and access
- Develop data architecture aligned with cloud (Azure, AWS, GCP) and hybrid environments
2. Data Strategy & Governance
- Partner with leadership to define data strategy, roadmap, and operating model
- Establish and enforce data governance frameworks including data quality, metadata, lineage, and stewardship
- Ensure compliance with regulatory requirements (e.g., PDPA, GDPR where applicable)
3. Data Integration & Engineering
- Design and oversee data pipelines (batch and real-time)
- Define patterns for data ingestion, transformation, and orchestration
- Enable integration across enterprise systems (ERP, CRM, Core, digital platforms)
4. Analytics & AI Enablement
- Architect data platforms that support BI, advanced analytics, and AI/ML workloads
- Enable self-service analytics through governed data access
- Collaborate with data scientists and analysts to optimize data usability
5. Technology & Innovation
- Evaluate and recommend data technologies, tools, and platforms
- Champion modern architecture (e.g., data mesh, lakehouse, event-driven architecture)
- Drive automation, scalability, and performance optimization
6. Stakeholder Engagement
- Collaborate with business, IT, and leadership stakeholders to translate requirements into data solutions
- Provide technical leadership and mentorship to data engineers and architects
- Communicate architecture decisions and trade-offs effectively
Requirement
- Bachelor's or Master's degree in Computer Science, Information Systems, or related field
- 8–12+ years of experience in data management, architecture, or engineering
- Proven experience designing enterprise-scale data architecture
- Strong knowledge of:
- Data modeling (Kimball, Inmon, Data Vault)
- ETL/ELT processes and tools
- SQL, NoSQL databases
- Big data technologies (e.g., Spark, Hadoop, Snowflake, Databricks)
- Hands-on experience with cloud data platforms (Azure Synapse, Databricks, Snowflake, BigQuery)
- Knowledge of data governance tools (e.g., Collibra, Purview, Alation)
- Familiarity with streaming platforms (Kafka, Event Hub)
- Experience with DevOps/DataOps practices
- Understanding of API-based and microservices architectures
