大数据开发工程师

该职位来源于猎聘 主要职责：  大数据仓库：设计并构建进入原始数据层的摄取管道，在核心数据模型中实施数据清洗和维度建模，并开发特定领域的数据集市。  业务分析与数据映射：将复杂的银行业务需求转化为清晰的技术规范，并定义跨数据仓库各层的完整源到目标映射。  数据产品交付：实施面向银行运营、金融产品和监管报告的稳健、特定领域的数据模型和产品。  项目管理：领导敏捷/Scrum冲刺，管理技术债务，并与全球产品和工程团队协调交付时间表。 主要要求：  经验：5年以上数据工程经验（或在数据密集型环境中担任技术业务分析师），其中3年以上专注于银行、金融科技或金融服务领域。  技术栈：精通SQL、Python、Java、Airflow、Spark和S3。  项目与需求管理：具备收集需求、定义数据规范、领导工程冲刺以及在Jira中管理待办事项的成熟经验。  英语：流利/专业英语（书面和口头），以实现无缝的跨境协作。 Key Responsibilities:  Big Data Warehouse: Design and build ingestion pipelines into raw data layers, implement data cleansing and dimensional modeling within the core data model, and develop domain-specific data marts.  Business Analysis & Data Mapping: Translate complex banking business requirements into clear technical specifications and define comprehensive Source-to-Target Mappings across data warehouse layers.  Data Product Delivery: Implement robust, domain-specific data models and products tailored for banking operations, financial products, and regulatory reporting.  Project Management: Lead Agile/Scrum sprints, manage technical debt, and coordinate delivery timelines with global product and engineering teams.

Key Requirements:  Experience: 5 years of experience in Data Engineering (or as a Technical BA in data-heavy environments), with 3 years specifically within banking, fintech, or financial services.  Tech Stack: Expertise in, SQL, Python, Java, Airflow, Spark and S3.  Project &

Requirements Management: Proven experience gathering requirements, defining data specifications, leading engineering sprints, and managing backlogs in Jira.  English: Fluent/Professional English (written and verbal) for seamless cross-border collaboration.