The Company
Our client is seeking a Senior Data Engineering Manager - Databricks, APAC to lead the design, migration, and modernization of the regional data platform. This role will move existing data platforms, pipelines, and analytics workloads onto Databricks, while building a scalable foundation for AI and Generative AI use cases across APAC.

The Role
- Lead the end-to-end migration of data platforms, data warehouses, data lakes, data marts, and data pipelines onto Databricks
- Define and implement the target lakehouse architecture using Databricks, Delta Lake, Unity Catalog, Databricks SQL, and modern data engineering patterns
- Own the migration roadmap, technical design, execution plan, sequencing, and cutover strategy
- Re-platform and modernize legacy ETL / ELT pipelines into scalable Databricks-native pipelines
- Build reusable frameworks for ingestion, transformation, orchestration, testing, data quality, and monitoring
- Establish best practices for data modelling, performance optimization, lineage, metadata management, and platform reliability
- Design and deploy AI and Generative AI capabilities on top of the Databricks platform
- Build secure and governed data foundations to support AI use cases across business functions
- Enable use cases such as enterprise search, natural-language querying, document intelligence, analyst copilots, and AI-assisted reporting
- Support Retrieval-Augmented Generation patterns using trusted enterprise data, embeddings, vector search, and governed data access
- Work with technology, security, and business stakeholders to define responsible AI controls including access management, data protection, auditability, monitoring, and cost controls
- Lead regional data engineering initiatives across APAC, ensuring delivery of platform, analytics, and AI-related projects
- Partner with business stakeholders to translate data needs into scalable technical solutions
- Work with global technology, architecture, security, analytics, and business teams to align regional delivery with enterprise standards
- Drive adoption of CI/CD, Git-based development, automated testing, DataOps, and production support processes

Your Profile
- At least 8 years of experience in data engineering, data platforms, cloud data architecture, or related technology roles
- Strong hands-on experience with Databricks, including lakehouse architecture, Delta Lake, Unity Catalog, Databricks SQL, workflows, and pipeline development
- Proven experience leading or supporting large-scale migration onto Databricks or another modern cloud data platform
- Strong experience designing and building data pipelines, data lakes, data warehouses, and analytics platforms
- Strong programming skills in SQL and Python; experience with PySpark is highly preferred
- Good understanding of data modelling, data governance, data quality, lineage, access control, and platform performance
- Experience with CI/CD, Git, automated testing, DevOps / DataOps, and production-grade data engineering practices
- Exposure to AI / ML / GenAI use cases including Retrieval-Augmented Generation, vector search, model serving, MLflow, or AI platform integration
- Experience in cloud environments such as AWS, Azure, or GCP
- Experience with BI / analytics tools such as Power BI, Tableau, Databricks dashboards, or similar platforms
- Exposure to AI governance, responsible AI, data privacy, and secure AI deployment practices
- Strong stakeholder management skills with the ability to work across regional and global teams
- Excellent communication skills and ability to explain technical concepts to technical and non-technical stakeholders
- Ability to operate as both a strategic platform owner and hands-on technical leader

Apply Today
Please send your resume, in WORD format only and quote reference number Ref No 67020-0013460646, by clicking the apply button. Please note that only short-listed candidates will be contacted.

Robert Half International Pte Ltd. Co. Registration no.: 200612189E | EA Licence no.: 07C5595 | Dmitriy Chervinskyi EA Registration no.: R22108655

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