Data Engineer

Architect and build robust, scalable data pipelines to ingest and process billions of trade-level PV calculations from various stress engines.

Develop and optimize large-scale aggregation jobs using Apache Spark, ensuring high performance and efficiency.

Design and deliver a suite of "intelligent data APIs" that provide flexible, on-demand access to both aggregated and non-aggregated risk data for teams across the firm.

Integrate Natural Language Processing (NLP) capabilities to create intuitive, query-based interfaces for data exploration, lowering the barrier to entry for complex analytics.

Load and model massive aggregated datasets into high-performance OLAP engines like Apache Pinot, Apache Druid, and Trino.

Build powerful, interactive analytical tools and dashboards on top of the OLAP layer, providing summary views and lightning-fast drill-down capabilities.

Partner directly with senior stakeholders in the Front Office, Quantitative teams, and Risk Management to understand their analytical needs and deliver innovative solutions.