Principal Engineer – AI & Data Platform (Online Travel Industry)

Salary: ฿360,000 – ฿500,000 per month

Roles & Responsibilities

• Lead the development of AI-powered data querying solutions, including natural language interfaces and text-to-SQL applications.

• Design, develop, and scale data quality tools and frameworks to ensure data accuracy, reliability, and trustworthiness.

• Architect and optimize analytical databases, query engines, and large-scale data infrastructure.

• Drive query performance optimization, data modeling, and query execution improvements.

• Collaborate with Technical Program Managers (TPMs) and cross-functional stakeholders to define technical strategies, roadmaps, and architecture.

• Lead complex engineering initiatives across AI applications, data quality systems, and analytical platforms.

• Mentor engineers, promote best practices, and establish high technical standards across data engineering and platform development.

• Improve data governance, observability, and reliability across the broader data platform.

Requirements

• 10+ years of experience in software engineering, data engineering, or related fields.

• Strong hands-on expertise in SQL and large-scale data systems.

• Experience with modern analytical databases or data warehouses such as StarRocks, Snowflake, BigQuery, or ClickHouse.

• Proficiency in backend programming languages such as Python, Java, Scala, or similar.

• Experience developing or working with AI/LLM-based applications, including text-to-SQL, conversational interfaces, or AI copilots.

• Strong understanding of data modeling, query execution, and performance optimization.

• Experience building scalable data platforms or analytical infrastructure.

• Proven ability to lead cross-functional, high-impact technical initiatives.

• Strong technical leadership, problem-solving, mentoring, and communication skills.

• Ability to balance hands-on engineering responsibilities with strategic technical decision-making.

Good to Have

• Experience building text-to-SQL systems or AI-driven data interfaces.

• Experience implementing or scaling analytical engines such as StarRocks.

• Knowledge of data observability, data quality, or governance frameworks.

• Familiarity with dbt, Airflow, Spark, or similar data engineering tools.