远程工作雷达

财务数据工程师,AI/LLM

Financial Data Engineer, AI/LLM

AI开发工程明确接受中国求职者
公司Binance
薪资未公开
工作地点Hong Kong, Singapore, Taiwan
地域资格明确接受中国求职者
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间今天
数据来源Himalayas
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明确接受中国求职者:该职位的地域要求包含中国,可正常投递。

关于币安
币安是全球领先的区块链生态系统,运营着全球交易量最大的数字资产交易平台,为100多个国家和地区的3亿多用户提供服务。我们致力于构建更加开放的金融生态系统,提升全球金融产品的可及性。
币安正在持续构建面向全球用户的股票及相关金融市场产品。相关数据将服务于面向用户端的股票产品和币安AI业务场景。我们正在寻找具有股票市场经验的专业人士,共同构建可靠、可扩展的数据和金融AI能力。

职位概述
你将参与构建币安股票及相关金融市场业务的核心数据基础,负责从数据源发现、评估、采集、集成到统一建模、实时处理、质量治理和数据服务的全流程。除了完成定义好的集成工作,我们期望你利用行业专业知识,持续识别更好的数据源和技术解决方案,使新的市场、产品和数据能够快速可靠地服务于交易产品和AI场景。

职责

  • 对金融市场数据进行研究、技术评估、采集、集成、清洗、标准化、计算、存储和服务,涵盖证券主数据、实时和历史市场数据、基本面数据、公司行为、指数以及业务所需的产品和风险数据;负责源数据采集、原始数据保留,并稳定交付至知识工程流水线,处理公告、新闻和研究报告等类型的数据。
  • 设计可扩展的统一数据模型和集成框架,处理不同市场的交易日历、时区、货币、证券标识符、上市关系、生命周期和数据修正,支持新市场和数据源的快速接入。
  • 构建以Flink为核心的批流统一数据流水线,持续优化延迟、吞吐量、查询性能、稳定性与成本,同时支持交易产品、研究分析和AI场景。
  • 建立数据质量和SLA框架,负责数据的完整性、准确性、及时性、一致性和可追溯性;构建自动化对账、异常检测、监控告警、原始数据重放、补传和故障恢复能力。
查看英文原文

About Binance
Binance is the global leading blockchain ecosystem, operating the world's largest digital asset trading platform by volume, serving over 300 million users across 100+ countries and regions. We are committed to building a more open financial ecosystem and improving global access to financial services.
Binance is continuously building stock and related financial market products for global users. The relevant data will serve user-facing stock products and Binance AI business scenarios. We are seeking professionals with stock market experience to jointly build reliable, scalable data and financial AI capabilities.
Role Overview
You will participate in building the core data foundation for Binance's stock and related financial market businesses, responsible for the full pipeline from data source discovery, evaluation, ingestion, and integration to unified modeling, real-time processing, quality governance, and data services. Beyond completing defined integrations, we expect you to leverage industry expertise to continuously identify better data sources and technical solutions, enabling new markets, products, and data to serve trading products and AI quickly and reliably.
Responsibilities

  • Conduct research, technical evaluation, ingestion, integration, cleansing, standardization, computation, storage, and servicing of financial market data, covering securities master data, real-time and historical market data, fundamentals, corporate actions, indices, and business-required product and risk data; responsible for source ingestion, raw retention, and stable delivery to knowledge engineering pipelines for content-type data such as announcements, news, and research reports.
  • Design scalable unified data models and integration frameworks, handling different markets' trading calendars, time zones, currencies, security identifiers, listing relationships, lifecycles, and data corrections, supporting rapid onboarding of new markets and sources.
  • Build batch-stream unified data pipelines centered on Flink, continuously optimizing latency, throughput, query performance, stability, and cost, while supporting consumer trading products, research analysis, and AI scenarios.
  • Establish data quality and service level frameworks, taking responsibility for completeness, accuracy, timeliness, consistency, and traceability; build automated reconciliation, anomaly detection, monitoring and alerting, raw data replay, backfill, and fault recovery capabilities.
  • Evaluate different sources (vendors, exchanges, APIs, file feeds, compliance collection) for coverage, quality, stability, revision mechanisms, and technical fit; collaborate with product, procurement, legal, and compliance teams to clarify usage, display, derivative, retention, and redistribution boundaries; drive rational primary/backup source strategies and alternatives.
  • Define data semantics, metric definitions, and service contracts jointly with trading product, data platform, AI engineering, and algorithm teams, ensuring consistent and reliable usage of the same stock facts across different products.
  • Drive data engineering efficiency and technical quality improvements, including metadata, data lineage, automated testing, CI/CD, task orchestration, capacity governance, and AI-assisted development.

Requirements

  • Master's degree or above in Computer Science, Software Engineering, Mathematics, Statistics, or related field; 5+ years of experience in data development, big data, or data platforms.
  • Familiar with stock markets and the investor research and decision-making workflow; understand trading mechanisms, market data, fundamentals and financial reports, corporate actions, valuation, and major market events; able to explain the complete pipeline of at least one type of financial data from source to user-facing product and key quality risks.
  • Proficient in SQL and Flink, with experience in large-scale real-time data processing, performance tuning, stability governance, and production issue troubleshooting.
  • Proficient in at least one of Java, Scala, or Python; familiar with Kafka, Spark, and ClickHouse, Doris, HBase, Elasticsearch, or other distributed storage and analytics technologies.
  • Familiar with data modeling, task scheduling, metadata, data lineage, data governance, and service levels; able to independently resolve cross-system data consistency issues.
  • High standards for data quality; able to design reproducible reconciliation, anomaly detection, backfill, and degradation strategies — not just completing data development tasks.
  • Experience with data source selection or production ingestion; able to articulate trade-offs between build vs. buy, multi-source verification, vendor dependency, and alternative solutions.
  • Strong business understanding and cross-team collaboration skills; able to translate trading, risk, research, or AI problems into clear data models and data contracts.

Bonus

  • Experience with stock data at brokerages, market data services, financial data, wealth management, or fintech platforms.
  • Familiarity with US stock market structure, trading calendars, pre/post-market sessions, corporate actions, and adjustment rules; experience with other stock markets also a plus.
  • Data experience with stock-related derivatives, ETFs, indices, or tokenized products.
  • Experience building low-latency market data pipelines, securities master data platforms, multi-market data models, quantitative research platforms, or large-scale backtesting data systems.
  • Experience with data anomaly detection, knowledge graphs, financial entity alignment, or building high-quality financial datasets for LLMs and retrieval-augmented generation (RAG).

Working at Binance

• Be a part of the world’s leading blockchain ecosystem that continues to grow and offers excellent career development opportunities
• Work alongside diverse, world-class talent in an environment where learning and growth opportunities are endless
• Tackle fast-paced, challenging and unique projects
• Work in a truly global organization, with international teams and a flat organizational structure
• Competitive salary and benefits
• Flexible working hours, remote-first, and casual work attire
Learn more about how Binancians embody the organization’s core values, creating a unified culture that enables collaboration, excellence, and growth.
Apply today to be a part of the Web3 revolution!

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.
Originally posted on Himalayas

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