Principal Data Engineer

(*) Must have:1. AI software development Experienced developing AI algorithm or understand how it works from scratch Developed an Application Programming Interface as an internet service Operated and manipulated an API service by using an appropriate software Controlled and tuned accuracy through operating data 2. Data engineering Data Warehousing ETL Processes Cloud Platforms (AWS, Azure, GCP) Python SQL Big Data Technologies (Hadoop, Spark, Kafka) Data Modeling Data Quality Data Security Version Control (Git) 3. Tools  Configuration management: Terraform CI/CD: GitHub Actions Monitoring and logging: Datadog, Cloud Monitoring, CloudWatch Project management: JIRA Cloud, Miro,... Documentation: Kibela, Google Workspace Spark: 2-3 years of experience Airflow: 1 year (As a user not administrator) 4. Cloud architecture Experienced developing a system by using some cloud services on AWS, GCP or Azure(AWS is preferable). Understood cloud service components from architectural perspective(To know what can do, how it works and what should be paid attention) Designed and integrated a system with appropriate security. (*) Nice to have: Good Communication skill and open-mind Good at English (four skills)