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Quant Developer - Trading Systems
Quant Developer - Trading SystemsNuvama Group • hosur, tamil nadu, in
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Quant Developer - Trading Systems

Quant Developer - Trading Systems

Nuvama Group • hosur, tamil nadu, in
6 days ago
Job description

Purpose

Design and build high-performance trading systems and data infrastructure from the ground up for Nuvama's capital markets operations. This role combines quantitative finance expertise with cutting-edge Data Engineering to create real-time trading execution systems, market data pipelines, and risk management platforms that directly impact trading profitability and operational efficiency.

1. Functional Responsibilities / KPIs

Primary Responsibilities

  • Trading System Development : Build live trading execution systems, order management platforms, and order book management systems from scratch
  • Real-time Data Infrastructure : Design and implement high-throughput market data ingestion and preprocessing pipelines using Databricks and AWS
  • Backtesting Frameworks : Develop comprehensive backtesting and simulation engines for strategy validation across multiple asset classes
  • Solution Architecture : Create scalable system designs that handle market volatility and high-frequency data streams
  • Trader Collaboration : Work directly with traders and portfolio managers to understand requirements and build custom solutions
  • Performance Optimization : Ensure ultra-low latency execution and real-time risk monitoring capabilities

Key Performance Indicators

  • System Performance : Achieve sub-millisecond latency for critical trading operations
  • Data Accuracy : Maintain 99.99% data integrity across all market data feeds
  • System Uptime : Deliver 99.9% availability during market hours with zero trading halts due to system issues
  • Processing Throughput : Handle 1M+ market data updates per second during peak trading
  • Project Delivery : Complete trading system modules within agreed timelines
  • Trader Satisfaction : Achieve 90%+ satisfaction scores from trading desk stakeholders.
  • 2. Qualifications

    Educational Requirements

  • Bachelor's / Master's degree in Computer Science, Engineering, Mathematics, Physics, or Quantitative Finance
  • Strong foundation in data structures, algorithms, and system design principles
  • Understanding of financial markets, trading mechanics, and quantitative methods
  • Technical Certifications (Preferred)

  • AWS certifications (Solutions Architect, Developer, or Developer)
  • Databricks certifications in data engineering or analytics
  • Financial industry certifications (CQF, FRM) are advantageous
  • 3. Experience

    Required Experience

  • 2-5 years of hands-on experience in quantitative finance or financial technology
  • Recent experience (within last 2 years) working with equity markets and trading systems
  • Proven track record of building trading systems, backtesting frameworks, or market data infrastructure
  • Experience with high-frequency data processing and real-time streaming systems
  • Direct collaboration experience with trading desks or portfolio management teams
  • Preferred Experience

  • Previous experience at investment banks, hedge funds, prop trading firms, or fintech companies
  • Experience building systems from scratch rather than maintaining legacy applications
  • Background in algorithmic trading strategy development and implementation
  • Exposure to Indian capital markets (NSE / BSE) and regulatory requirements (SEBI compliance)
  • Leadership experience in technical projects or mentoring junior developers
  • 4. Functional Competencies

    Programming & Development

  • Expert-level proficiency in at least 2 of : PySpark, Scala, Rust, C++, Java
  • Python ecosystem : Advanced skills in pandas, numpy, scipy for quantitative analysis
  • Performance optimization : Experience with memory management, parallel processing, and low-latency programming
  • API development : RESTful and WebSocket APIs for real-time market data distribution
  • Data Engineering & Infrastructure

  • AWS services : EC2, S3, RDS, Kinesis, Lambda, CloudFormation for scalable deployments
  • Database technologies : Time-series databases (InfluxDB, TimescaleDB), columnar stores (ClickHouse), traditional RDBMS
  • Streaming technologies : Real-time data processing frameworks (Kafka, Kinesis, Apache Spark Streaming)
  • Trading Systems Architecture

  • Order Management Systems : Order routing, execution algorithms, and trade lifecycle management
  • Market Data Processing : Tick data ingestion, order book reconstruction, and market microstructure analysis
  • Risk Management : Real-time position monitoring, limit checking, and risk control systems
  • Backtesting Frameworks : Zipline, Backtrader, QuantConnect, bt, PyAlgoTrade, and custom framework development
  • Financial Markets Knowledge

  • Equity Markets : Order types, market microstructure, settlement cycles, and trading regulations
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    Quant Developer • hosur, tamil nadu, in

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