Senior Associate / Assistant VP, AI Data Engineer (Snowflake Semantic Layer)

About the role

Temasek is looking for a Senior Associate / Assistant Vice President, AI Data Engineer to build the Snowflake semantic layer that underpins its AI agents and analytics. The role sits at the intersection of data engineering, data modelling and AI systems engineering, defining metrics, entities and relationships so that AI agents, BI tools and analysts draw on a single, governed source of truth. It works across structured investment data and unstructured sources such as research reports and company filings.

Key responsibilities

• Define the technical strategy and reference architecture for the Snowflake semantic layer, including metric and dimension standards, and how agents consume it via Cortex Agents and Snowflake Intelligence
• Build and deliver semantic views, data pipelines (Apache Airflow, AWS services) and tuned Cortex Agents, and drive answer accuracy through verified query libraries and evaluation sets
• Apply dimensional modelling best practices (Kimball, star schemas, conformed dimensions) and explore AI-assisted tooling such as Cortex Code and Semantic View Autopilot
• Lead and mentor a small squad of engineers, own sprint planning and delivery
• Embed RBAC, row and column-level security, lineage and audit logging, and set metric ownership, certification and change-management processes
• Monitor semantic view usage, agent behaviour, answer accuracy, data quality and cost
• Work with business, investment, governance, cybersecurity and enterprise architecture teams to agree metric definitions and share patterns and best practices
• Track trends in Snowflake's semantic and Cortex capabilities and recommend adoption of tools such as dbt Semantic Layer, ontologies and knowledge graphs

Required profile

• 5-8 years in data engineering, analytics engineering or data architecture, including at least 2 years building semantic or metrics layers in production
• Experience leading engineers and working across business, governance, security and architecture stakeholders
• Exposure to financial services or investment data is a strong plus

Required skills

• Snowflake: data modelling, performance and cost tuning, RBAC and security, semantic views, Cortex Analyst, Cortex Agents, Cortex Search; Snowflake Intelligence is a plus
• Apache Airflow and AWS (S3, IAM, Lambda, Glue) integrated with Snowflake
• dbt, CI/CD for data assets, dimensional modelling, advanced SQL
• Python and SQL; experience producing LLM-based data applications (text-to-SQL, RAG, agentic workflows)