30. Data Engineer [µðÁöÅÐ ÇコÄÉ¾î ½ºÅ¸Æ®¾÷]
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[´ã´ç¾÷¹«] - Design, build and manage data infrastructure including data lakes, warehouses, and databases to harness extensive medical data resources. [ÀÚ°Ý¿ä°Ç] - Proficiency in Python and SQL. - Basic knowledge of statistics and machine learning concepts. - Excellent problem-solving skills, attention to detail, and the ability to work both independently and collaboratively. [¿ì´ë»ç] - Experience with cloud-based data platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc. - Experience with data pipelines and orchestration tools like Airflow, Prefect, Dagster, etc. - Experience with analytics/visualization tools such as Tableau, Power BI, Grafana, Streamlit, etc. - Experience with Git and Github for version control and collaboration. - Experience with Docker and Docker Compose for software containerization and orchestration. - Experience with medical or healthcare data. |
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