6 months ago
Singapore, SingaporeStaff+
Responsibilities
- Define and advise on modern data architectures aligned with business goals and supporting AI, analytics, and automation.
- Guide adoption of cloud-native and hybrid data solutions across AWS, Azure, GCP, Snowflake, and Databricks.
- Provide thought leadership on data modeling, data warehousing, lakehouse, data mesh, data fabric, and serverless architectures.
- Lead data governance frameworks covering security, compliance, ethical AI, metadata, data catalogs, data quality, and lineage.
- Advise on real-time streaming, AI/ML-enabled data architectures, feature engineering, model-training pipelines, graph databases, NoSQL, and data integration.
- Act as a trusted advisor to C-level executives and business leaders while collaborating with data scientists, engineers, analysts, and IT leaders.
- Lead assessments of emerging data technologies and shape strategies that future-proof organizational data ecosystems.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field.
- 10–16 years of experience in data architecture, data engineering, or cloud-based data solutions.
- Deep knowledge of cloud data platforms including AWS Redshift, Azure Synapse, Google BigQuery, and Snowflake.
- Expertise in data governance, master data management, compliance frameworks, AI-ready architectures, ETL/ELT, data integration, and workflow automation.
- Experience advising on real-time data streaming with Kafka, Kinesis, or Pub/Sub.
- Familiarity with TOGAF and Zachman data architecture frameworks.
- Flexibility to travel within the Southeast Asia/Asia Pacific region.
- Preferred qualifications include cloud data certifications, experience with Data Mesh and Data Fabric architectures, knowledge of MongoDB, Neo4j, and Cassandra, and background in data ethics, responsible AI, and AI governance frameworks.
Benefits
- Locations include Singapore, Kuala Lumpur, Jakarta, and Bangkok.
- Requires travel within the Southeast Asia/Asia Pacific region.
- More experienced candidates may be considered for Principal/Director-level appointment.
Tech Stack
Amazon RedshiftApache CassandraApache KafkaAWSAzureDatabricksGoogle BigQueryGoogle Cloud PlatformMongoDBNeo4jSnowflake
Categories
Data Engineering
