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5~6 years experience with data engineer and soft engineer. (Distributed Queue System, Database, Web Crawling, RESTful API, ETL, Docker, CICD, Grafana & Prometheus, GCP, GKE, Airflow ...etc.)

1~2 years experience with ML and DL.

FinMind github project， 2,000 stars.

出版 Python 書籍 - Python 大數據專案 X 工程 X 產品 資料工程師的升級攻略

NDHU

Sr. Data Engineer

linsam

17LIVE

Senior Data Engineer (IC5)

• Refactor ETL, create a airflow project by Cloud Composer to transfer ETL tools from digdag to airflow and transfer ETL develop method from shell script to python.
• Maintenance BigQuery more than 100 tables.
• Create pipelines from mysql and mongo to bigquery.
• Create a good development culture, including the introduction of CICD, dev-stage-uat-master, release news, unit tests and test coverage.
• Using Airflow unified scheduler job, like cloud function scheduler, bq scheduler, crontab, and ML model by R or Python ...etc.
• Create Data Team's first real-time ETL system via GKE, Pub/Sub and Memorystore for sending push notifications to users.
• Reduce Data Team 25% cost.
• Keep SLO above 98.
• Create Data Team's first API via GKE for ML model, include achieve graceful shutdown, and run stress test via ApacheBench, and setup auto-scaling by hpa. 95% latency is under 200ms and RPS is over 200.
• Create a Tagging System for tracking groups of users. 
• Create a BigQuery Resource Monitor to monitor users BQ slot and query count usage. 
• The finalists of Break the Norm awards on 2021-Q3 and 2021-Q4. 
• Assist in interview more than 10 new data engineer. 
• Mentor junior data engineers to be more effective individual contributors.
• Apply the data team's models to the company's APP. (automatically send push notifications and in-app messages)
• Automatically update recommend streamer list via data team's models to the company's APP.

開發 python/C# 下單 API。
開發分散式系統、log監控、流量監控、警報等功能。
開發模擬交易系統。
開發逐筆交易、零股交易 API。

永豐金證券

Software Engineer

1. https://tripresso.com 公司網站。
2. 我開發的 ML model，估計讓公司訂單增加3%左右。
3. 維護 20 台分散式 ETL 系統。
4. 優化 ETL 系統，減少50%的時間。
5. 製作分析圖表，提供不同部門參考。


• Analysis travel data and build a machine learning model. Estimating increase 3% orders (revenue).
• Maintain and develop an ETL distributed queuing system with 20 machines.
• Optimize the ETL system reduced more than 50% execution time.
• Develop new product crawler let product volume increase 1.5%.
• Making analysis charts provide for other departments.


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