Financial Data Engineer, Stock & AI Data (APAC Remote)

About the role

Binance is building stock and related financial market products for global users, and needs a Financial Data Engineer to build its core data foundation. You will own the full pipeline, from source discovery, ingestion and integration to unified modelling, real-time processing, quality governance and data services, and will keep looking for better data sources and technical solutions so trading products and AI can be served quickly and reliably.

Key responsibilities

• Ingest, cleanse, standardise and compute financial market data (securities master data, real-time and historical market data, fundamentals, corporate actions, indices, product and risk data) and deliver it to knowledge-engineering pipelines for announcements, news and research reports.
• Design scalable unified data models and integration frameworks for trading calendars, time zones, currencies, security identifiers, listing relationships and data corrections.
• Build batch-stream pipelines centred on Flink, optimising latency, throughput, query performance, stability and cost.
• Set up data quality and service-level frameworks, including automated reconciliation, anomaly detection, monitoring, alerting, raw data replay, backfill and fault recovery.
• Evaluate vendors, exchanges, APIs, file feeds and compliance collections, and work with product, procurement, legal and compliance teams on usage, display, derivative, retention and redistribution boundaries.
• Define data semantics, metric definitions and service contracts with trading, data platform, AI engineering and algorithm teams.
• Improve data engineering efficiency through metadata, data lineage, automated testing, CI/CD, task orchestration, capacity governance and AI-assisted development.

Required profile

• Masters' degree or above in Computer Science, Software Engineering, Mathematics, Statistics or a related field.
• 5+ years of experience in data development, big data or data platforms.
• Familiarity with stock markets and investor research workflows, and the ability to explain a financial data pipeline from source to product.
• Strong data quality standards, with reproducible reconciliation, anomaly detection and backfill strategies.
• Experience selecting data sources or ingesting data, and strong cross-team collaboration.

Required skills

• Proficiency in SQL and Flink, with large-scale real-time data processing and performance tuning.
• At least one of Java, Scala or Python.
• Familiarity with Kafka, Spark, ClickHouse, Doris, HBase, Elasticsearch or similar distributed storage and analytics technologies.
• Data modelling, task scheduling, metadata, data lineage, data governance and service levels.

What we offer

• Remote-first, flexible working hours and casual work attire.
• Competitive salary and benefits.
• A global organisation with a flat structure and international teams.