Financial Data Engineer, AI/LLM

This is a fully remote position, open to applicants in Taiwan.

📋 Description

• Conduct research, perform technical evaluations, ingest, integrate, cleanse, standardize, compute, store, and manage financial market data.

• Manage securities master data, as well as real-time and historical market data, fundamentals, corporate actions, indices, and product and risk data.

• Ingest, preserve, and reliably deliver announcements, news, and research reports to knowledge engineering pipelines.

• Develop scalable unified data models and integration frameworks that account for markets, trading calendars, time zones, currencies, security identifiers, listing relationships, lifecycles, and data corrections.

• Construct and optimize batch-stream unified data pipelines focused on Flink.

• Enhance latency, throughput, query performance, stability, and cost-effectiveness for trading products, research analysis, and AI applications.

• Establish frameworks for data quality and service levels, encompassing completeness, accuracy, timeliness, consistency, and traceability.

• Implement automated reconciliation, anomaly detection, monitoring and alerting, raw data replay, backfill, and fault recovery functionalities.

• Assess vendors, exchanges, APIs, file feeds, and sources for compliance collection.

• Collaborate with product, procurement, legal, and compliance teams regarding data usage, display, derivatives, retention, and redistribution parameters.

• Define data semantics, metric definitions, and service contracts in coordination with trading product, data platform, AI engineering, and algorithm teams.

• Enhance metadata, data lineage, automated testing, CI/CD, task orchestration, capacity governance, and AI-assisted development.

⛳️ Requirements

• A Master's degree or higher in Computer Science, Software Engineering, Mathematics, Statistics, or a related field.

• Over 5 years of experience in data development, big data, or data platforms.

• Knowledge of stock markets and workflows related to investor research and decision-making.

• Comprehension of trading mechanisms, market data, fundamentals, financial reports, corporate actions, valuation, and significant market events.

• Capability to explain the entire pipeline of at least one type of financial data from source to user-facing product, along with key quality risks.

• Expertise in SQL and Flink.

• Experience in large-scale real-time data processing, performance optimization, stability governance, and troubleshooting production issues.

• Proficiency in at least one programming language such as Java, Scala, or Python.

• Familiarity with technologies like Kafka, Spark, ClickHouse, Doris, HBase, Elasticsearch, or other distributed storage and analytics solutions.

• Understanding of data modeling, task scheduling, metadata, data lineage, data governance, and service levels.

• Ability to independently resolve cross-system data consistency challenges.

• Skill in designing reproducible reconciliation, anomaly detection, backfill, and degradation strategies.

• Experience with selecting data sources or managing production ingestion.

• Capability to articulate trade-offs between building versus buying solutions, multi-source verification, vendor reliance, and alternative approaches.

• Strong business acumen and collaborative skills across teams.

• Ability to translate trading, risk, research, or AI challenges into clear data models and contracts.

🏝️ Benefits

• Competitive salary and comprehensive benefits package.

• Flexible working hours.

• Remote-first work environment.

• Casual dress code.

• Excellent opportunities for career advancement.

• Opportunities for learning and personal growth.

• A diverse environment filled with world-class talent.