Responsibilities
Data Architecture & Strategy
- Define and advise on the design of modern, future-ready data architectures that align with business goals and support AI, analytics, and automation.
- Guide organizations in adopting cloud-native and hybrid data solutions (AWS, Azure, GCP, Snowflake, Databricks).
- Provide thought leadership on best practices for data modeling, data warehousing, and lakehouse architectures to ensure scalability and performance.
- Shape long-term data strategies that foster flexibility, innovation, and interoperability across platforms.
Data Governance & Advisory
- Lead the development of governance frameworks and policies that ensure data security, compliance, and ethical AI use.
- Provide guidance on the creation and maintenance of data dictionaries, metadata management, and data cataloging, ensuring consistency, accuracy, and alignment with industry best practices.
- Advise on data quality management strategies, ensuring robust data lineage, accuracy, and reliability across the organization.
- Define governance roadmaps that support AI adoption while maintaining compliance with various compliance framework and regulation.
Cloud & Emerging Technologies
- Provide strategic recommendations on leveraging data lakes, data meshes, and serverless architectures to optimize data processing and storage.
- Advise on implementing real-time streaming solutions (Kafka, Kinesis, Pub/Sub) to support AI-driven analytics.
- Assess and recommend AI/ML-enabled data architectures that facilitate scalable feature engineering and model training pipelines.
- Guide organizations in evaluating and adopting graph databases, NoSQL solutions, and modern data integration tools.
Collaboration & Leadership
- Work with C-level executives and business leaders, translating complex data challenges into strategic initiatives.
- Collaborate with data scientists, engineers, and business analysts to enhance data accessibility and usability.
- Drive innovation in data architecture, ensuring organizations remain competitive and AI-ready.
- Lead assessments of emerging data technologies and best practices to future-proof organizational data strategies.
Any other ad-hoc duties as assigned by supervisor
Requirement
Required Skills & Qualifications
- Experience in data architecture, data engineering, or cloud-based data solutions.
- Flexibility to travel within SEA/Asia Pacific region
Technical & Advisory Expertise:
- Deep knowledge of cloud data platforms (AWS Redshift, Azure Synapse, Google BigQuery, Snowflake).
- Expertise in data governance, master data management (MDM), and compliance frameworks.
- Strong understanding of AI-ready data architectures and their impact on feature engineering and ML workflows.
- Ability to guide organizations on ETL/ELT strategy, data integration, and workflow automation.
- Familiarity with industry-standard data architecture frameworks (TOGAF, Zachman).
- Experience advising on real-time data streaming (Kafka, Kinesis, Pub/Sub).
Preferred Qualifications
- Certifications in cloud data platforms (AWS Certified Data Analytics, Azure Data Engineer, GCP Professional Data Engineer).
- Experience advising on Data Mesh and Data Fabric architectures.
- Knowledge of Graph databases and NoSQL solutions (MongoDB, Neo4j, Cassandra).
- Background in data ethics, responsible AI, and AI governance frameworks.
Interested applicants, please email your resume to Andre Chua Jing Ming
Email: [Confidential Information]
CEI Reg No: R1989053
EA Licence No: 99C4599
Recruit Express Pte Ltd
