Senior Financial Data Engineer

Binance; Singapore; Remote; SGD 180,000 - 240,000; Full time

Benefits offered by this job

Work-from-home arrangement

Competitive salary

Flat structure

Job summary

Binance is hiring a senior data engineer to build and maintain the core data infrastructure for stock and market data. You will oversee ingestion, cleansing, modeling, and serving of real-time and historical market data, including quotes, fundamentals, and corporate actions.

The role requires strong SQL and Flink skills and experience with distributed storage technologies. You will design scalable data models, ensure data quality, and work with product, legal, and compliance to define data usage

Qualifications

• Master's degree or above in Computer Science, Software Engineering, Mathematics, Statistics, or a related field.
• Familiar with stock markets and investor research workflow; understands trading mechanics, market quotes, fundamentals and corporate actions.
• Proficient in SQL and Flink, with experience in large-scale real-time data processing, performance tuning, stability governance.
• Proficient in Java, Scala, or Python; familiar with Kafka, Spark, and distributed storage/analytics technologies such as ClickHouse, Doris, HBase, Elasticsearch.
• Familiar with data modeling, metadata, data governance, and service levels; able to independently resolve cross-system data consistency issues.
• Experience with data source selection or production ingestion; articulate trade-offs between buy vs. build, multi-source verification, and fallback alternatives.
• Strong business understanding and cross-team collaboration skills; translate trading, risk, research, or AI problems into clear data models and contracts.

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.
• Design scalable unified data models and ingestion frameworks handling market conventions, time zones, currencies, security identifiers, and lifecycle events.
• Build batch-stream unified data pipelines centered on Flink, optimizing latency, throughput, and cost for trading products, research, and AI use cases.
• Establish data quality and service-level frameworks with completeness, accuracy, timeliness, consistency, and traceability; enable automated reconciliation and anomaly detection.
• Evaluate coverage and quality of various data sources; collaborate with product, procurement, legal, and compliance to define usage boundaries and fallback strategies.
• Partner with trading product, data platform, AI engineering, and algorithm teams to define data semantics, metrics, and service contracts across products.
• Drive data engineering efficiency, including metadata management, data lineage, automated testing, CI/CD, and capacity governance.

Skills

SQL

Flink

Java/Scala/Python

Data modeling

Data governance

Data lineage

Education

Master's degree or above in CS/SE/Math/Stats

Tools

Kafka

Spark

ClickHouse

Doris

HBase

Elasticsearch

Job description

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 experience in large-scale real-time data processing, performance tuning, stability governance, and production issue troubleshooting.

Proficient in at least one of Java, Scala, or Python; familiar with Kafka, Spark, and distributed storage/analytics technologies such as ClickHouse, Doris, HBase, Elasticsearch, or similar.

Familiar with data modeling, task scheduling, metadata, data lineage, data governance, and service levels; able to independently resolve cross-system data consistency issues.

Holds high standards for data quality, capable of designing reproducible reconciliation, anomaly detection, backfill, and degradation strategies—not just completing data development tasks.

Has experience with data source selection or production ingestion, able to articulate trade-offs between buy vs. build, multi-source verification, vendor dependency, and fallback alternatives.

Strong business understanding and cross-team collaboration skills; able to translate trading, risk, research, or AI problems into clear data models and data contracts.

Qualifications

Experience with stock data at brokerages, market data services, financial data providers, wealth management, or fintech platforms.

Familiar with US equity market structure, trading calendars, extended hours, corporate actions, and adjustment rules; experience with other stock markets is also a plus.

Experience with stock-related derivatives, ETFs, indices, or tokenized products.

Has built low-latency market data pipelines, securities master data platforms, multi-market data models, quantitative research platforms, or large-scale backtesting data systems.

Experience with data anomaly detection, knowledge graphs, financial entity alignment, or constructing high-quality financial datasets for large language models and retrieval-augmented generation (RAG).

Why Binance

• Shape the future with the world’s leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.

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