Data Engineer

Data Engineer

Thai Insurance Research and Development Co., Ltd. (TIRD) • Phra Khanong, Bangkok • Reports to Head of Enterprise Data Solutions

Help Build the Future of Insurance Data in Thailand!!!

Are you a problem solver who loves working with data? Do you enjoy fixing messy systems, improving performance, and building new data platforms from the ground up?

We're looking for a Data Engineer who's ready to roll up their sleeves and tackle real-world challenges — from messy pipelines and performance bottlenecks to cloud modernization and data governance.

Key Responsibilities

• Design, develop, and maintain robust data pipelines using Apache Airflow, SSIS, PySpark, and Talend to ingest, transform, and load large-scale datasets (300M+ rows) from multiple sources.

• Manage and optimize relational databases including Oracle and SQL Server, ensuring high performance and scalability for analytical workloads.

• Design, build, and maintain cloud data platforms and warehousing solutions using AWS services such as Redshift and S3, alongside ClickHouse for high-performance analytical querying.

• Develop and maintain OLAP solutions using SSAS for advanced reporting and analytics, including cube design, partitioning, and aggregation strategies.

• Implement ETL processes for structured and semi-structured data, ensuring data quality, consistency, and compliance with industry standards.

• Collaborate with the BI Team, Actuarial Team, and business stakeholders to understand requirements and deliver efficient data models and solutions.

• Monitor and improve data pipeline performance, troubleshoot bottlenecks, and implement best practices for parallel processing and resource optimization.

• Ensure data security and compliance with insurance industry regulations and company policies.

• Leverage big data technologies such as Apache Spark for distributed processing and advanced data transformations.

• Automate workflows and scheduling using Airflow DAGs, ensuring reliability and scalability of data operations.

• Document data architecture, processes, and standards, and provide technical guidance to team members.

Required Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field.

• 3-5 years of experience building and maintaining data pipelines.

• Proficiency in SQL and experience with relational databases (Oracle, SQL Server), including performance tuning and query optimization.

• Hands-on experience with ETL tools such as SSIS, Talend, and PySpark, and data modeling for OLAP solutions using SSAS.

• Knowledge of data pipeline orchestration using Apache Airflow.

• Experience with big data processing frameworks such as Apache Spark for distributed data transformations.

• Hands-on experience with cloud database/data platform services such as AWS Redshift, S3, and ClickHouse.

• Solid understanding of data warehousing concepts, star/snowflake schema, and partitioning strategies for large datasets (300M+ rows).

• Proficiency in Python or another scripting language for automation and data manipulation.

• Knowledge of data quality, governance, and security best practices.

• Ability to work with large-scale data and optimize workflows for performance and scalability.

• Familiarity with insurance industry data or other regulated environments is a plus.

Preferred Qualifications

• Experience with Power BI and building efficient data marts.

• Experience with data privacy, governance, and secure data access practices.

• Hands-on with additional cloud platforms/tools such as Azure, Databricks, Delta Lake, Snowflake, or the Hadoop ecosystem.

• Able to troubleshoot performance issues in both backend pipelines and frontend analytics tools.

• Comfortable working in a fast-paced, high-ownership environment with cross-functional teams.

Why Join Us

• Build Thailand's insurance data infrastructure from the ground up — real ownership over pipelines and platforms that power an entire industry, not just one company.

• Work with a modern, varied tech stack (Airflow, Spark, AWS, ClickHouse) and real scale (300M+ row datasets), with room to modernize legacy systems your way.

• Close collaboration with BI and Actuarial teams gives you direct visibility into how your data work drives business and industry decisions.