【金融科技】Data Team Lead

10/03更新

百仕聯股份有限公司本公司其他工作

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應徵

應徵人數 0~5 人

工作內容

-Lead and mentor a team of data engineers in building and maintaining scalable ETL pipelines, ensuring data integrity and security. -Drive infrastructure planning and design for data platforms to ensure performance, scalability, and reliability. -Collaborate with business and engineering teams to define data requirements, design data models, and drive the development of data products. -Lead efforts in optimizing data systems for performance, scalability, and cost-efficiency across multiple environments, including cloud (GCP) and on-premises data centers. -Oversee the entire lifecycle of data projects, from conception to deployment, ensuring timely and high-quality delivery. -Take ownership of the continuous improvement of our data infrastructure and engineering practices to meet the needs of a rapidly growing business. -Provide technical guidance on the adoption of new technologies and data platforms to drive innovation in the team.

職務類別

、

工作待遇

待遇面議

（經常性薪資達 4 萬元或以上）

工作性質

全職

雇用類型

代企業徵才

代徵企業

其它軟體及網路相關業

上班地點

台北市松山區信義路五段7號57樓 (台北101辦公大樓）

遠端工作

管理責任

管理4人以下

出差外派

無需出差外派

上班時段

日班

休假制度

週休二日

可上班日

不限

需求人數

1人

條件要求

工作經歷

5年以上

學歷要求

大學以上

科系要求

不拘

語文條件

不拘

擅長工具

不拘

工作技能

不拘

其他條件

-You have 5+ years of relevant experience in data engineering, including at least 2 years of team leadership or mentorship experience. -Proven track record of designing, building, and maintaining complex ETL pipelines with a focus on scalability, reliability, and security. -Strong proficiency in backend development with expertise in shell scripting, SQL, and at least one programming language (e.g., Python, Scala). -Expertise in distributed computing engines and platforms (e.g., ClickHouse, PySpark, Kafka, BigQuery, Airflow). -Demonstrated experience in planning and implementing infrastructure for large-scale data processing and storage solutions. -Familiarity with data exploration and visualization tools (e.g., Superset, Tableau) and experience in implementing data lake and data warehouse architectures. -Practical experience with cloud-based data processing solutions (e.g., AWS Data Pipelines, GCP Dataflow). -Practical experience with CDC (Capture Data Change) tools and methodologies, or any other streaming solutions. -Experience in managing stakeholders at different levels, with excellent interpersonal and communication skills. -Previous experience in setting up or utilizing Data Catalogs is a plus. -Passion for team development, fostering a collaborative and high-performance culture. Tech skills: Shell、Python、Scala、Data Modeling、ETL、MS SQL、MySQL、Tableau

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