15 days ago
Pune, IndiaStaff+
Responsibilities
- Architect and build scalable data pipelines that ingest and process billions of trade-level PV calculations.
- Develop and optimize large-scale Apache Spark aggregation jobs.
- Design and deliver APIs for aggregated and non-aggregated risk data access.
- Integrate NLP capabilities for query-based data exploration and analytics.
- Load and model large datasets in Apache Pinot, Apache Druid, and Trino.
- Build interactive analytical tools and dashboards with summary and drill-down views.
- Collaborate with front-office, quantitative, and risk management stakeholders.
- Lead technical projects and resolve complex data and access issues.
Requirements
- 10+ years of experience with strong Python, Java, and/or Scala programming skills and expert-level SQL.
- A degree in a quantitative or technical field such as Computer Science, Financial Mathematics, or Financial Engineering.
- Expert hands-on experience with big data technologies, particularly Apache Spark.
- Proven experience with high-performance OLAP databases such as Apache Pinot, Apache Druid, or Trino.
- Strong knowledge of computer science fundamentals, including data structures and algorithms.
- Experience or strong interest in applying Natural Language Processing to data access and analytics.
- Highly desirable experience in financial services, market risk, derivatives, and risk calculations such as VaR, stress testing, and PV.
- Ability to solve complex problems independently, lead technical projects, and communicate with senior business and quantitative stakeholders.
Tech Stack
Categories
BackendData Engineering
About Citi
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