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WE'RE HIRING Data Engineer 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 using tools such as Talend and PySpark, ensuring data quality, consistency, and compliance with industry standards. • Collaborate with 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+ 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). • Familiarity with insurance industry data or other regulated environments (preferred). • 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. Preferred Qualifications • Experience with Power BI and building efficient data marts. • Experience with data privacy, governance, and secure data access practices. • Hands-on with cloud platforms or tools such as AWS (Redshift, S3), ClickHouse, Azure, Databricks, Delta Lake, Snowflake, or 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.