Data Engineer

We are a digital health therapeutics company operating across SEA, focused on the intersection of mental health and physical chronic diseases. We combine behavioral science, psychology, data science, and digital design to help companies, healthcare providers, and ultimately, people, achieve a healthier lifestyle. We are looking for a proactive and skilled Data Engineer to help build and scale our data infrastructure from the ground up. You will play a key role in designing and developing a modern data warehouse using AWS Redshift and DBT, consolidating multiple data sources into a single source of truth that powers decision-making across the company. You’ll join a fast-moving team in a startup environment, where autonomy, problem-solving, and a builder mindset are essential. What You’ll Do

Design, build, and maintain robust, scalable ETL / ELT pipelines using DBT, Python, and SQL Set up and manage a cloud-based data warehouse using AWS Redshift Ingest and integrate data from a variety of sources (e.g., APIs, application databases, third-party tools) Implement and document data warehouse rules for each layer (staging, intermediate, and reporting) Apply data cleaning practices, including handling missing values using appropriate imputation techniques Build and enforce data quality validation checks to ensure reliable downstream analytics Collaborate with data scientists, analysts, and business stakeholders to translate needs into efficient data models Maintain a secure, performant, and cost-effective infrastructure using AWS tools (e.g., S3, Lambda, IAM) Write clear, well-maintained documentation for data models, pipelines, and infrastructure What We’re Looking For

2–3 years of experience in data engineering Proficiency in SQL for data modeling, transformation, and performance optimization Strong experience with AWS services (especially Redshift, S3, Lambda, IAM) Hands-on experience with DBT, understanding layer-based modeling and modular design Programming experience in Python, especially for data ingestion and transformation Familiarity with data cleaning techniques, including strategies for dealing with missing or inconsistent values Ability to document and maintain data warehouse rules and logic for transparency and governance Comfort working independently with minimal supervision in a fast-paced startup environment Strong attention to detail and a commitment to data integrity and reliability Clear communication skills and the ability to work cross-functionally with technical and non-technical stakeholders Bonus Points For

Experience with orchestration tools Familiarity with data lake architecture and partitioning strategies Knowledge of CI / CD for data workflows Experience working with event-driven or streaming data Familiarity with BI tools like Metabase, Tableau, or Looker Understanding of data access controls, compliance, and governance best practices Why Join Us

You’ll work on meaningful, high-impact problems across the business You’ll shape the company's data foundation and standards from the ground up You’ll be part of a collaborative, ownership-driven culture with room to grow You’ll have autonomy and visibility in a supportive, startup-minded environment

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