Manager - Data Engineer AI

Responsibilities: Develop, establish, and enforce data engineering standards for data pipelines, emphasizing modular design, code reuse, testability, and maintainability. Align the data engineering roadmap with the organization’s strategic objectives to drive data-driven decision making and AI/ML model development. Lead modernization initiatives, such as transitioning from Data Lake to Lakehouse architectures and adopting advanced orchestration and streaming technologies, to ensure long-term scalability. Oversee the creation and maintenance of comprehensive documentation, runbooks, and governance artifacts to support audits, compliance, and operational excellence. Implement and oversee comprehensive testing strategies, including data transformations, quality gates, and end-to-end validation processes. Build and manage CI/CD pipelines for data code and infrastructure, ensuring automated testing, version control, and rollback capabilities. Standardize on orchestration and transformation frameworks (e.g., Talend ETL, Spark, Databricks, AWS Glue) to promote consistency, reusability, and best practices. Ensure the stable, reliable, and efficient day-to-day operation of data platforms and pipelines, including proactive monitoring, incident management, change management, and SLA adherence. Drive data privacy, security, and compliance by implementing robust access controls, encryption, audit trails, and regulatory adherence. Optimize cloud data infrastructure for cost efficiency and performance, including effective data lifecycle management and storage tiering. Foster the development and deployment of scalable data pipelines and feature stores that enable AI and machine learning models, ensuring data quality, lineage, and accessibility for AI/ML teams. Qualifications: Bachelor's Degree in Computer Science, Computer Engineering, other technical discipline, or equivalent work experience 5-10 years of experience in Data Engineering, Data Warehousing, or related fields, with hands-on experience designing and orchestrating data workflows using Talend ETL or Spark, along with a solid understanding of cloud-based data engineering. Proven experience in building data pipelines and feature stores to support AI and machine learning models. Advanced experience designing and orchestrating data integration workflows using Talend ETL. Deep understanding of modern data architecture, including batch and streaming ingestion patterns. Extensive experience with big data processing frameworks such as Apache Spark (preferably on AWS Glue and Databricks). Proficiency in programming and scripting languages, especially Python, Scala, or Java. Practical experience with AWS cloud ecosystem, including services like S3, RDS, Redshift, Athena, and AWS Glue. Strong SQL skills, with experience managing enterprise relational databases (e.g., MSSQL, Oracle, PostgreSQL, and NoSQL). Proven experience developing data pipelines and feature stores to support AI and machine learning workflows. Good English skills at business level About Krungthai-AXA Life Insurance Krungthai-AXA Life Insurance Public Company Limited, created from a solid co-investment partnership between Krungthai Bank PCL. and the AXA Group, global financial protection and asset-management specialists. The trademark of Krungthai-AXA Life Insurance is designed to indicate the combination of the two corporations. Krung Thai Bank PCL. and AXA Group logos are aligned with Thai characters displaying the company name as Krungthai-AXA Life Insurance placed above the red line and the new company signature. Redefining/Life Insurance. Today Krungthai-AXA Life Insurance Public Company Limited is a fast-growing life insurance company with a vision – Ambition AXA. Our Perks and benefits Employee and Family Health Insurance Benefits Life and Accident Insurance Benefits Hybrid Working and Flexible Working Hours Annual Leave & Birthday Leave Salary Increment & Bonus Digital Learning - Self Learning Organization Annual Health Check up Provident Fund