Financial Data Engineer, Stock & AI Data

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🌐 Hong Kong, Australia, +2 more countries – Remote

🇭🇰 Hong Kong – Remote 🇦🇺 Australia – Remote 🇸🇬 Singapore – Remote 🇹🇼 Taiwan – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 11%

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Binance

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2017

₿ Crypto

💳 Fintech

💰 Initial Coin Offering on 2020-12

Crypto • Fintech

Binance is the world's leading cryptocurrency exchange, serving over 235 million registered users across more than 180 countries. The platform offers a wide array of services, including the trading of over 350 cryptocurrencies in Spot, Margin, and Futures markets. Users can also buy and sell crypto via Binance P2P, earn interest through Binance Earn, and engage in NFT trading on the Binance NFT marketplace. Binance provides low transaction fees and diverse payment options, making it a preferred choice for cryptocurrency enthusiasts worldwide.

📋 Description

• Research, technically evaluate, ingest, integrate, cleanse, standardize, compute, store, and service financial market data • Handle securities master data, real-time and historical market data, fundamentals, corporate actions, indices, and product and risk data • Manage source ingestion, raw retention, and stable delivery to knowledge engineering pipelines for announcements, news, and research reports • Design scalable unified data models and integration frameworks across markets • Handle trading calendars, time zones, currencies, security identifiers, listing relationships, lifecycles, and data corrections • Build and optimize batch-stream unified data pipelines centered on Flink • Optimize latency, throughput, query performance, stability, and cost for trading products, research analysis, and AI scenarios • Establish data quality and service-level frameworks • Build automated reconciliation, anomaly detection, monitoring and alerting, raw data replay, backfill, and fault recovery capabilities • Evaluate vendors, exchanges, APIs, file feeds, and compliance collection sources • Collaborate with product, procurement, legal, and compliance teams on data usage and redistribution boundaries • Define data semantics, metric definitions, and service contracts with trading product, data platform, AI engineering, and algorithm teams • Improve 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 • Familiarity with stock markets and investor research and decision-making workflows • Understanding of trading mechanisms, market data, fundamentals and financial reports, corporate actions, valuation, and major market events • Ability to explain the complete pipeline of at least one type of financial data from source to user-facing product and key quality risks • Proficiency in SQL and Flink • Experience with large-scale real-time data processing, performance tuning, stability governance, and production issue troubleshooting • Proficiency in at least one of Java, Scala, or Python • Familiarity with Kafka, Spark, and ClickHouse, Doris, HBase, Elasticsearch, or other distributed storage and analytics technologies • Familiarity with data modeling, task scheduling, metadata, data lineage, data governance, and service levels • Ability to independently resolve cross-system data consistency issues • High standards for data quality and ability to design reproducible reconciliation, anomaly detection, backfill, and degradation strategies • Experience with data source selection or production ingestion • Ability to articulate build-versus-buy, multi-source verification, vendor dependency, and alternative-solution trade-offs • Strong business understanding and cross-team collaboration skills • Ability 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 • Bonus: Familiarity with US stock market structure, trading calendars, pre/post-market sessions, corporate actions, and adjustment rules • Bonus: Data experience with stock-related derivatives, ETFs, indices, or tokenized products • Bonus: Experience building low-latency market data pipelines, securities master data platforms, multi-market data models, quantitative research platforms, or large-scale backtesting data systems • Bonus: Experience with data anomaly detection, knowledge graphs, financial entity alignment, or high-quality financial datasets for LLMs and RAG

🏖️ Benefits

• Excellent career development opportunities • Learning and growth opportunities • Competitive salary and benefits • Flexible working hours • Remote-first work arrangement • Casual work attire • Career growth and continuous learning • Work-from-home arrangement (may vary depending on the nature of the role and team)

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