Financial Data Engineer, AI/LLM

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, sta