Senior Data Architect
Summary
Designs and maintains enterprise data architecture, builds scalable data platforms (lakes, warehouses, streaming), and sets standards for modeling, governance, and cloud integration to support analytics and AI.
- 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
- 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)
- Design and oversee data pipelines (batch and real-time)
- Define patterns for data ingestion, transformation, and orchestration
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
- Strong knowledge of:
- 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