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Tier-1 brand, mid-level popular data role, metro location and broad skill demands increase competition.
Core data engineering skills are transferable but finance risk domain knowledge raises domain specificity.
Explicit 5+ years plus mandatory Spark, Java, OLAP and finance-domain expectations make filters strict.
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Architect and build scalable data pipelines handling billions of trade-level risk calculations using Apache Spark.
Develop and optimize large-scale aggregation jobs and deliver intelligent data APIs for flexible data access across the firm.
Integrate NLP and OLAP technologies to create interactive analytical tools and dashboards for senior stakeholders in Markets and Risk organizations.
5+ years of experience with Core Java, Apache Spark, Big Data Technologies including Hive.
Proven experience with high-performance OLAP databases such as Apache Pinot, Apache Druid, or Trino.
Degree in a quantitative or technical field like Computer Science, Financial Mathematics, or Financial Engineering.
Work Experience Required: 5+ years in relevant technologies and systems programming.
Senior technologist comfortable leading complex, large-scale data engineering projects for market risk analytics.
Experienced in financial domain, especially market risk, derivatives, and risk calculations like VaR and Stress Testing.
Hands-on expert in Java/Scala, big data ecosystems, data structures, algorithms, and AI/NLP application in data analytics.