软件工程师
Software Engineer
我们正在寻找一位具备数据工程经验的资深软件工程师，加入一个在金融领域开发大规模解决方案的国际团队。该职位涉及在基于云的环境中构建稳健、可扩展且易于维护的数据管道和服务。你将作为跨职能、高性能团队的一员，参与实时和高吞吐量数据系统的开发。
作为一支快速成长且充满活力的团队，我们重视积极主动、自主驱动、注重细节的专业人士，他们能够在独立工作的同时兼顾整体产品愿景。
关键职责：
- 为数据工程团队设计和开发微服务（基于Java，运行在Kubernetes上）
- 构建和维护高性能的ETL工作流和数据摄入逻辑
- 处理数据速度、重复、模式验证/版本控制以及可用性问题
- 集成第三方数据源以丰富金融数据
- 与跨职能团队协作，统一数据消费格式和标准
- 优化数据存储、查询和交付，满足内部和外部用户需求
- 维护服务和管道的可观测性和监控
要求：
- 3年以上数据工程和管道开发经验，处理过大量数据
- 3年以上Java开发经验（生产环境）
- 具备使用云原生工具进行ETL工作流和数据处理的经验
- 精通SQL，熟悉关系型和非关系型数据库，以及性能优化
- 具备使用监控工具（如Prometheus、Grafana、Datadog）的经验
- 熟悉Kubernetes、Kafka、Redis、Snowflake、Clickhouse、Apache Airflow
- 理解软件工程原则和面向对象设计
- 能够独立且主动工作，具备良好的沟通能力
加分项：
- 有金融科技或交易相关行业的背景
- 计算机科学或相关技术领域的学位
- 具备高可用性基础设施设计经验
项目简介：
这是一个长期的金融科技项目，专注于交易数据监控和欺诈检测。工程团队分布在多个国家，使用现代云原生技术。你将加入一个重视责任、清晰度和产品思维的环境。
最初发布于Himalayas
查看英文原文
We are looking for a strong Software Engineer with experience in data engineering to join an international team working on large-scale solutions in the financial domain. This role involves building robust, scalable, and maintainable data pipelines and services in a cloud-based environment. You’ll be part of a cross-functional, high-performance team working with real-time and high-volume data systems.
As part of a fast-growing and dynamic team, we value people who are proactive, self-driven, and detail-oriented professionals who can work independently while keeping the broader product vision in mind.
Key Responsibilities:
- Design and develop microservices for the data engineering team (Java-based, running on Kubernetes)
- Build and maintain high-performance ETL workflows and data ingestion logic
- Handle data velocity, duplication, schema validation/versioning, and availability
- Integrate third-party data sources to enrich financial data
- Collaborate with cross-functional teams to align data consumption formats and standards
- Optimize data storage, queries, and delivery for internal and external consumers
- Maintain observability and monitoring across services and pipelines
Requirements:
- 3+ years in data engineering and pipeline development with large volumes of data
- 3+ years of experience with Java (in production environments)
- Experience with ETL workflows and data processing using cloud-native tools
- Strong knowledge of SQL, relational and non-relational databases, and performance optimization
- Experience with monitoring tools (e.g., Prometheus, Grafana, Datadog)
- Familiarity with Kubernetes, Kafka, Redis, Snowflake, Clickhouse, Apache Airflow
- Solid understanding of software engineering principles and object-oriented design
- Ability to work independently and proactively, with strong communication skills
Nice to Have:
- Background in fintech or trading-related industries
- Degree in Computer Science or related technical field
- Experience with high-availability infrastructure design
About the project:
This is a long-term FinTech project focused on trade data monitoring and fraud detection. The engineering team is distributed across several countries and works with modern cloud-native technologies. You'll be part of an environment that values accountability, clarity, and product thinking.
Originally posted on Himalayas