{"id":1249067,"url":"https://alion.io/job/temasek-senior-associateassistant-vice-president-ai-data-engineer","title":"Senior Associate/Assistant Vice President, AI Data Engineer","company":{"id":232841,"name":"Temasek","domain":"temasek.com.sg","url":"https://alion.io/company/temasek","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"head","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":61000,"max_usd":149000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":99},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Chroma","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Function Calling","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Great Expectations","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Neo4j","optional":false},{"name":"OCR","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Polars","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"SQLAlchemy","optional":false},{"name":"Weaviate","optional":false},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-08-30T02:00:00Z","employer_posted_date":"2026-08-30","last_verified_at":"2026-10-25T19:48:27Z","board_verified":true,"closed_at":null,"days_open":56,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":56},"description":"Temasek is a global investment company headquartered in Singapore, with a net portfolio value of S$518 billion (US$401b, €350b, £304b, RMB2.77t) as at 31 March 2026. Our Purpose “So Every Generation Prospers” guides us to make a difference for today’s and future generations. We seek to build a resilient and forward-looking portfolio that will deliver good sustainable returns over the long term.\nWe have 13 offices in 9 countries around the world: Beijing, Hanoi, Mumbai, Shanghai, Shenzhen, and Singapore in Asia; and Brussels, London, Mexico City, New York, Paris, San Francisco, and Washington, DC outside Asia.\nFor more information on Temasek, please visit www.temasek.com.sg\nFor Temasek Review 2026, please visit www.temasekreview.com.sg\nFor Sustainability Report 2026, please visit www.temasek.com.sg/SR2026\n Introduction\nAI agents are only as good as the data they can reason over. Poorly structured, stale, or inconsistently governed data is the most common reason enterprise AI products fail to deliver value - not model capability, but data readiness. The AI Data Engineer at Temasek is responsible for building the data foundations that make Temasek's agentic AI systems trustworthy, accurate, and capable of reasoning over the complex, heterogeneous data environment of a global investment institution.\nThis role sits at the intersection of data engineering and AI systems engineering - responsible for designing and building the data architectures, pipelines, and quality frameworks that allow AI agents to retrieve, reason over, and act on Temasek's investment data. You will work across structured investment data (portfolio positions, financial statements, market data), unstructured data (research reports, company filings, meeting notes, news), and real-time data streams - making all of it accessible, reliable, and AI-readable.\nResponsibilities\nAgent-ready data architecture\nDesign and build data architectures specifically optimised for AI agent consumption: structured data stores accessible via tool-calling APIs, vector knowledge bases for semantic retrieval, graph databases for relationship-based reasoning, and hybrid retrieval systems that combine keyword, semantic, and structured query approaches.\nBuild and maintain the data layer for Temasek's RAG (Retrieval-Augmented Generation) pipelines: document ingestion workflows, chunking strategy design, embedding generation and refresh pipelines, metadata tagging for filtered retrieval, and vector index management across multiple knowledge domains (company research, market intelligence, portfolio data, regulatory filings).\nDesign the ontology and schema standards for AI-accessible data assets - ensuring that data structures are consistent, well-documented, and interpretable by AI agents without requiring ad-hoc parsing or custom logic in every product that consumes them.\nArchitect real-time and near-real-time data feeds for AI agents that require current information: market data integration, news and research feed ingestion, portfolio event streaming, and alert-triggering data pipelines - with latency and freshness SLAs defined and enforced.\nEnterprise data quality and governance\nDefine and implement data quality standards for AI-consumed data assets: completeness checks, consistency validation, freshness monitoring, and anomaly detection - with automated quality gates that prevent degraded data from entering AI production systems.\nBuild and maintain comprehensive data lineage tracking across all AI data pipelines - enabling full traceability from raw source to AI agent consumption, supporting both operational debugging and regulatory audit requirements.\nPartner with the AI Security & Governance Lead and the enterprise data governance function to ensure AI data assets comply with Temasek's data classification standards, access control requirements, and cross-border data handling rules - particularly for data used in China-facing AI workflows.\nDesign and operate data observability tooling: pipeline health monitoring, data drift detection, schema change alerting, and SLA dashboards that give AI product teams visibility into the data their systems depend on.\nConduct regular data quality reviews with AI product teams - identifying where data gaps or quality issues are limiting AI product performance, and prioritising data engineering investment to address the highest-impact gaps.\nShared, reusable data platform for AI\nBuild reusable data assets and services that multiple AI products can depend on - including a shared investment knowledge graph, a company and market data API layer, a document intelligence pipeline for research and filing ingestion, and a portfolio analytics data service.\nMaintain and evolve a data catalogue for AI-accessible data assets: documenting sources, schemas, freshness, quality metrics, access procedures, and known limitations - enabling AI product managers and engineers to make informed decisions about which data to use and trust.\nContribute to Temasek's enterprise data platform strategy from an AI-first perspective - advocating for data architecture decisions that serve AI consumption patterns, not just conventional BI and reporting use cases.\nEngage with external data vendors and market data providers to evaluate, onboard, and maintain data sources that improve the quality and coverage of AI agent knowledge bases - conducting ongoing vendor data quality assessments and managing data licensing agreements in coordination with procurement.\nRequirements\nExperience and background\n4-8 years of data engineering experience with at least 2 years specifically focused on building data infrastructure for AI/ML or LLM-powered systems in production.\nDemonstrated experience at a data-intensive organisation with complex, heterogeneous data environments - financial data, enterprise data platforms, or equivalent - ideally with exposure to investment data domains (company financials, market data, portfolio systems).\nHands-on experience building RAG pipelines or AI knowledge bases in production, including vector store management, embedding pipeline design, and chunking strategy optimisation.\nStrong data engineering fundamentals: pipeline design and orchestration, schema design, data quality frameworks, and lineage tracking - with the rigour expected of a Palantir-calibre data engineering background.\nTechnical capabilities\nData pipeline and orchestration: Python (pandas, Polars, SQLAlchemy), dbt, Apache Airflow or Prefect, Spark for large-scale processing; experience with both batch and streaming pipeline architectures (Kafka, Kinesis, or equivalent).\nAI data stack: vector databases (Pinecone, Weaviate, pgvector, Chroma), embedding models and management, LlamaIndex or LangChain data connectors, document parsing and OCR tooling, and chunking strategy design for different document types.\nStructured data and analytics: SQL proficiency across multiple dialects, experience with enterprise data warehouse platforms (Snowflake, BigQuery, Redshift, or Databricks), and familiarity with graph database concepts (Neo4j or equivalent).\nData quality and observability: experience with data quality frameworks (Great Expectations, Soda, or equivalent), data lineage tools (OpenLineage, DataHub, Marquez), and data observability platforms (Monte Carlo, Acceldata, or equivalent).","description_format":"text","description_chars":7334,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Pension & Sovereign Wealth Funds","Investment Holding Companies"],"lifecycle":[{"event":"open","at":"2026-09-25T18:15:40Z"}],"visa":[],"liveness":{"score":21,"band":"cold","label":"Long shot","p_open":1,"p_active":0.614,"p_room":0.35,"age_days":56,"expected_fill_days":18,"reasons":["conf:4","win:tail"],"computed_at":"2026-10-25T05:49:26Z"},"pay":null,"html_url":"https://alion.io/job/temasek-senior-associateassistant-vice-president-ai-data-engineer","json_url":"https://alion.io/job/temasek-senior-associateassistant-vice-president-ai-data-engineer.json","meta":{"generated_at":"2026-10-25T21:23:29Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":30288,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-26T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":232841},"rest":"https://alion.io/mcp/rest/get_company?id=232841"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Ftemasek-senior-associateassistant-vice-president-ai-data-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Ftemasek-senior-associateassistant-vice-president-ai-data-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Ftemasek-senior-associateassistant-vice-president-ai-data-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/temasek-senior-associateassistant-vice-president-ai-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Ftemasek-senior-associateassistant-vice-president-ai-data-engineer"}]}