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