A real-time streaming analytics platform for trade surveillance, portfolio exposure, and market-data-derived pricing signals.
Added May 25, 2026
Last signal 14h ago
Trading and fintech teams struggle to turn high-volume financial and transactional data into reliable real-time analytics for desks, risk teams, and pricing systems. The signals point to repeated internal work around streaming pipelines, cross-exchange analytics, portfolio views, surveillance, and sub-second market data delivery.
StreamRisk would provide managed ingestion, normalization, and streaming computation for financial data sources such as trades, order books, portfolios, and transactional events. It would ship configurable modules for trade surveillance, exposure monitoring, VWAP/depth analytics, cross-exchange spreads, and low-latency feeds into dashboards or pricing algorithms.
Multiple companies are hiring senior engineers to build similar real-time financial data infrastructure in-house. The need is rising as crypto, trading, fintech, and asset-management teams require faster analytics, anomaly detection, and operational data pipelines.
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Risk Data Pipelines develops software on top of the core Risk Technology platform to handle market or asset-class specific processing, including: Trade Data Ingress - Normalize and stream trade data to Squarepoint's systems from trading platforms like Bloomberg, Fidessa and SpiderRock.
Data Engineering: Own the trade & position platform end-to-end — venue connectors, the Python + SQL data model, reconciliation, and data-quality controls. Risk & Analytics: Build a greenfield, next-generation risk platform — real-time risk monitoring, PnL/risk calculation, alerting, and circuit-breaking strategies.
Build the derived analytics the business runs on: cross-exchange spreads, VWAP at depth, order book microstructure for the desks; portfolio views, exposure, performance for wealth and asset management.
Experience building reliable distributed systems that process large volumes of financial or transactional data
Lead the architecture and development of streaming data pipelines that deliver market and operational data to pricing algorithms with sub-second latency, relying on technologies such as Kafka and Flink
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