Middle/Senior Data Engineer

Design, build, and optimize Apache Airflow DAGs for various domains (e.g., Legacy HCX, Master, Vendor, TPDD) to support robust data pipelines. - Migrate and harmonize client data from on-premise or legacy databases to PostgreSQL, and further to Snowflake, leveraging Amazon S3 as a staging layer. - Ensure data quality and schema consistency by implementing validation frameworks using Great Expectations. - Optimize existing ETL workflows for performance, accuracy, and cost-efficiency. Monitor and manage data pipeline health (e.g., CPI, Risk Learning, TR, Roombas, Grogu). - Integrate third-party data sources (e.g., SAM.gov Watchlist) into centralized data warehouses. - Deploy and maintain Infrastructure as Code (IaC) using AWS Cloud Development Kit (CDK), and support CI/CD pipeline deployments (e.g., CM Deployments). - Enable and maintain OpenSearch Sync for real-time or batch search indexing. - Collaborate closely with business analysts, data scientists, and client stakeholders to translate business needs into scalable and efficient data solutions. - Maintain comprehensive documentation and support version-controlled deployment of DAGs and data schema changes.

Package: at least 13 months/ year. Review twice per year. - Bonus: Tet bonus, project bonus, holiday bonus, HR referral bonus... - Participate in learning and training activities inside and outside the company, accumulate learning points, and develop G points on the company's management system. - Leave Saturday, Sunday + 12 days of leave/year - Clubs and many cultural sports art activities sponsored or supported by the company (For example Football, table tennis, badminton, swimming, music, English, games, etc.) - Ensure health: periodic health checks, support to buy high quality health insurance... - Join the Rikkei Care Health Insurance Plan. - Mental comfort: playing music on demand every day, fresh fruit, team building activities... Going out near and far everywhere - Opportunity to work abroad and travel around.

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. - Proven experience building and maintaining data pipelines using Apache Airflow. - Strong experience with PostgreSQL, Snowflake, and Amazon S3. - Familiarity with data validation frameworks like Great Expectations. - Hands-on experience with ETL optimization, monitoring, and debugging. - Proficiency with AWS services, especially in IaC using CDK. - Experience with CI/CD pipelines and modern deployment practices. - Understanding of OpenSearch or similar indexing/search technologies. - Excellent communication and collaboration skills.