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Tier-1 brand plus metro Pune increase competition, but heavy technical specialization limits applicant pool.
Core big-data skills are transferable, but market-risk and derivatives domain preference raises specialization sensitivity.
Explicit 10+ years, mandatory Spark/OLAP/Java/Python/SQL skills and finance domain preference make filters strict.
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Architect and build scalable data pipelines processing billions of trade-level Present Value (PV) calculations for risk analytics.
Develop high-performance aggregation jobs using Apache Spark and deliver intelligent data APIs for on-demand risk data access.
Integrate OLAP engines and NLP to create interactive analytical tools enabling senior stakeholders in Markets and Risk to make faster decisions.
10+ years programming experience with Python, Java and/or Scala, plus expert-level SQL.
Hands-on experience with big data technologies, especially Apache Spark, and high-performance OLAP databases like Apache Pinot, Druid, or Trino.
Degree in quantitative or technical field such as Computer Science, Financial Mathematics, or Financial Engineering.
Work Experience Required: 10+ years in relevant software development and big data analytics roles.
Proven ability to architect and deliver large-scale risk analytics data platforms in financial services environment.
Strong technical depth in big data processing, OLAP systems, and applying AI/NLP for intuitive data access.
Experience collaborating directly with senior quantitative, front-office, and risk stakeholders to build impactful analytical solutions.