Senior Financial Data Engineer

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.
Role Overview

You will help build the core data infrastructure for Binance 's stock and related financial market businesses, responsible for the full pipeline—from data source discovery, evaluation, and ingestion, to unified modeling, real-time processing, quality governance, and data services. Beyond completing predefined integrations, we expect you to continuously seek better data sources and technical solutions based on industry experience, enabling new markets, products, and data to serve trading products and AI quickly and reliably.

Responsibilities

Own the research, technical evaluation, ingestion, cleansing, standardization, computation, storage, and servicing of financial market data, covering securities master data, real-time and historical market quotes, fundamentals, corporate actions, indices, and product/risk data as required by the business. For content-type data such as announcements, news, and research reports, own source ingestion, raw retention, and stable delivery to the knowledge engineering pipeline.

Design scalable unified data models and ingestion frameworks that handle varying market conventions for trading calendars, time zones, currencies, security identifiers, listing relationships, lifecycle events, and data corrections, enabling 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-facing trading products, research and analysis, and AI use cases.

Establish data quality and service-level frameworks, taking ownership of completeness, accuracy, timeliness, consistency, and traceability. Build capabilities for automated reconciliation, anomaly detection, monitoring and alerting, raw data replay, backfill, and disaster recovery.

Evaluate the coverage, quality, stability, revision mechanisms, and technical compatibility of various data sources—including vendors, exchanges, APIs, file feeds, and compliant collection. Collaborate with product, procurement, legal, and compliance teams to define boundaries for usage, display, derivation, storage, and redistribution, and drive reasonable primary/backup source and fallback strategies.

Partner with trading product, data platform, AI engineering, and algorithm teams to jointly define data semantics, metric definitions, and service contracts, ensuring that the same stock facts can be used consistently and reliably across different products.

Drive data engineering efficiency and technical quality improvements, including metadata management, 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 a related field, with 5+ years of experience in data engineering, big data, or data platforms.

Familiar with stock markets and the investor research and decision-making workflow; understands trading mechanics, market quotes, fundamentals and financial reports, corporate actions, valuation, and major market events. Able to explain the full pipeline of at least one type of financial data from source to end-user product, including key quality risks.

Proficient in SQL and Flink, with expe