Work across all aspects of data from engineering to building sophisticated visualisations, machine learning models and experiments
Analyze and interpret large (PB-scale) volumes of transactional, operational and customer data using proprietary and open source data tools, platforms and analytical tool kits
Translate complex findings into simple visualisations and recommendations for execution by operational teams and executives
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Conduct research, technical evaluation, ingestion, integration, cleansing, standardization, computation, storage, and servicing of financial market data, covering securities master data, real-time and historical market data, fundamentals, corporate actions, indices, and business-required product and risk data; responsible for source ingestion, raw retention, and stable delivery to knowledge engineering pipelines for content-type data such as announcements, news, and research reports.
Design scalable unified data models and integration frameworks, handling different markets' trading calendars, time zones, currencies, security identifiers, listing relationships, lifecycles, and data corrections, supporting 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 trading products, research analysis, and AI scenarios.
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