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Tier-1 brand and metro location but senior, specialized data skillset limits applicant density.
Requires deep big-data and market-risk domain experience, limiting cross-industry transferability.
Explicit 10+ years and mandatory Spark/OLAP/data platform experience will tightly filter candidates.
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Architect and build scalable data pipelines processing billions of trade-level Present Value calculations from stress engines.
Develop intelligent APIs and integrate OLAP and NLP technologies for rapid, flexible risk data access and analytics.
Collaborate with senior front-office and risk stakeholders to deliver high-performance analytics solutions supporting critical market risk calculations like FRTB and historical VaR.
10+ years of programming experience with Python, Java and/or Scala and expert-level SQL skills.
Hands-on expertise with big data technologies, especially Apache Spark.
Experience with high-performance OLAP databases such as Apache Pinot, Apache Druid, or Trino.
Degree in quantitative/technical field (e.g., Computer Science, Financial Mathematics, Financial Engineering).
Senior technologist with strong background in large-scale data engineering for finance, particularly market risk and derivatives.
Experienced in designing AI-integrated analytics systems, including NLP-driven data access interfaces.
Proven ability to independently lead complex technical projects and collaborate effectively with senior quantitative and business stakeholders.