面議(經常性薪資達4萬元或以上) 台北市大同區 2年工作經驗 1天前更新
We are seeking 2 Data Engineers to join our core data team, focusing on the Finance & Fraud domain. In this role, you will build and maintain robust data pipelines to support Business Intelligence efforts, transforming financial data for analysis, reporting, and initiatives related to financial insights, compliance, and fraud prevention. If you are passionate about data engineering and its critical impact on financial integrity and fraud detection, we encourage you to apply.
Key Responsibilities
• Design, develop, and optimize data pipelines, ETL processes, and data models (e.g., in Snowflake) for efficient data ingestion, transformation, and querying.
• Implement and maintain data quality checks and monitoring to ensure data accuracy and consistency.
• Develop interactive dashboards and reports using Power BI to visualize KPIs and insights for stakeholders.
• Leverage Google Cloud Platform (GCP) and Terraform to build, deploy, and automate scalable and reliable data solutions and infrastructure.
• Collaborate with finance and fraud prevention teams to understand data requirements and deliver solutions supporting financial reporting, compliance, and fraud detection.
• Ensure the security and integrity of sensitive financial data throughout its lifecycle within data pipelines and storage.
Technical Requirements (Must-Have)
• Strong proficiency in SQL and data warehousing and data modeling concepts (e.g., Data Vault, Star Schema).
• Proficiency in Python.
• Familiarity with ETL tools and data integration techniques.
• Hands-on experience with cloud technologies (e.g., GCP, Airflow).
• Proficient use of big data technologies (e.g., Snowflake).
• Software development best practices (GIT, CI/CD, pair programming, etc.).
• Experience with infrastructure as code (e.g., Terraform).
• Expertise in Power BI.
Nice-to-Have Skills
• Experience with Agile development methodologies.
• Certifications in relevant technologies (e.g., GCP).
• Strong communication and collaboration skills.
• Experience with financial data analytics, reporting, or fraud detection systems.
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