Lead Data Engineer

Lead Data Engineer

About Fullerton Health Group and Fullerton Health Technology (FHT)

Fullerton Health Group is a leading integrated healthcare provider across Asia-Pacific, operating an extensive network of clinics, third-party administrators (TPAs), and integrated healthcare services across multiple markets.

Fullerton Health Technology (FHT) serves as the Group's technology and innovation arm, spearheading enterprise AI transformation, data platform modernization, and intelligent healthcare automation initiatives across the region.

Our mission is to re-architect healthcare operations through AI — spanning intelligent claims processing, document understanding, agentic workflow automation, and next-generation data platforms.

Working place: Ho Chi Minh office, 127 Hong Ha, Duc Nhuan ward, Vietnam.

Role Overview:

We are hiring a Lead Data Engineer to drive the enterprise data strategy supporting AI transformation and data-driven decision excellence across healthcare operations. You will have the opportunity to work alongside one of Southeast Asia's leading AI teams, applying cutting-edge AI and LLM technologies to solve complex, real-world healthcare challenges at scale. From enabling agentic automate processing to building AI-ready data lakes, this role sits at the core of our regional AI transformation journey.

Key Responsibilities:

Architecture Leadership:

- Define enterprise Data Lake architecture

- Lead cross-border data integration

- Enable real-time data pipelines and streaming architecture

- Implement data quality monitoring and observability mechanisms

- Develop metadata management and data catalog strategy

- Enable self-service analytics and executive dashboards

- Standardize API-based data exchange across internal systems

Governance & Compliance:

- Define data governance standards

- Ensure PDPA and regulatory compliance

- Establish data access control frameworks

AI Enablement:

- Design scalable AI-ready data infrastructure

- Build AI/ML feature stores and model data pipelines

- Establish AI-Ops and Data-Ops best practices

- Leverage AI technologies to understand data semantics, recognize data structures, and enhance data completeness and quality

- Apply AI-driven approaches to transform raw data into structured datasets, enabling automated reporting and actionable insights

Team Leadership:

- Build and scale Data Engineering teams

- Define coding standards and best practices

- Collaborate with Ops /IT teams

Requirements:

- 8–12+ years in data engineering

- Experience designing enterprise-scale data platforms

- Strong cloud architecture experience (Azure, GCP, AWS)

- Experience building and managing large-scale data lakes, data warehouses, and real-time pipelines

- Strong understanding of data governance, security, and regulatory compliance (e.g., PDPA or equivalent)

- Experience working in multinational / foreign enterprises with cross-border collaboration exposure

- Excellent written and spoken English; able to communicate effectively with regional and global stakeholders

- Experience collaborating with Product, IT Operations, Data Science, AI Engineering, and Business teams.

- Experience implementing DataOps / MLOps / AIOps frameworks

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