Financial Data Engineer, AI/LLM
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Job Description
Financial Data Engineer building stock-market data infrastructure for Binance’s blockchain ecosystem. Developing Flink pipelines and reliable datasets for trading products and AI applications.
Responsibilities:
- 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
- Ingest, retain, and stably deliver announcements, news, and research reports to knowledge engineering pipelines
- Design scalable unified data models and integration frameworks across markets, 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 covering completeness, accuracy, timeliness, consistency, and traceability
- 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, display, derivative, retention, 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 in 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, 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
- Ability to design reproducible reconciliation, anomaly detection, backfill, and degradation strategies
- Experience with data source selection or production ingestion
- Ability to articulate trade-offs between build vs. buy, multi-source verification, vendor dependency, and alternative solutions
- Strong business understanding and cross-team collaboration skills
- Ability to translate trading, risk, research, or AI problems into clear data models and data contracts
Benefits:
- Competitive salary and benefits
- Flexible working hours
- Remote-first work arrangement
- Casual work attire
- Excellent career development opportunities
- Learning and growth opportunities
- Diverse, world-class talent environment
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