Quant Developer

PurposeDesign 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/KPIsPrimary ResponsibilitiesTrading System Development: Build live trading execution systems, order management platforms, and order book management systems from scratchReal-time Data Infrastructure: Design and implement high-throughput market data ingestion and preprocessing pipelines using Databricks and AWSBacktesting Frameworks: Develop comprehensive backtesting and simulation engines for strategy validation across multiple asset classesSolution Architecture: Create scalable system designs that handle market volatility and high-frequency data streamsTrader Collaboration: Work directly with traders and portfolio managers to understand requirements and build custom solutionsPerformance Optimization: Ensure ultra-low latency execution and real-time risk monitoring capabilitiesKey Performance IndicatorsSystem Performance: Achieve sub-millisecond latency for critical trading operationsData Accuracy: Maintain 99.99% data integrity across all market data feedsSystem Uptime: Deliver 99.9% availability during market hours with zero trading halts due to system issuesProcessing Throughput: Handle 1M+ market data updates per second during peak tradingProject Delivery: Complete trading system modules within agreed timelinesTrader Satisfaction: Achieve 90%+ satisfaction scores from trading desk stakeholders.2. QualificationsEducational RequirementsBachelor's/Master's degree in Computer Science, Engineering, Mathematics, Physics, or Quantitative FinanceStrong foundation in data structures, algorithms, and system design principlesUnderstanding of financial markets, trading mechanics, and quantitative methodsTechnical Certifications (Preferred)AWS certifications (Solutions Architect, Developer, or Developer)Databricks certifications in data engineering or analyticsFinancial industry certifications (CQF, FRM) are advantageous3. ExperienceRequired Experience2-5 years of hands-on experience in quantitative finance or financial technologyRecent experience (within last 2 years) working with equity markets and trading systemsProven track record of building trading systems, backtesting frameworks, or market data infrastructureExperience with high-frequency data processing and real-time streaming systemsDirect collaboration experience with trading desks or portfolio management teamsPreferred ExperiencePrevious experience at investment banks, hedge funds, prop trading firms, or fintech companiesExperience building systems from scratch rather than maintaining legacy applicationsBackground in algorithmic trading strategy development and implementationExposure to Indian capital markets (NSE/BSE) and regulatory requirements (SEBI compliance)Leadership experience in technical projects or mentoring junior developers4. Functional CompetenciesProgramming & DevelopmentExpert-level proficiency in at least 2 of: PySpark, Scala, Rust, C++, JavaPython ecosystem: Advanced skills in pandas, numpy, scipy for quantitative analysisPerformance optimization: Experience with memory management, parallel processing, and low-latency programmingAPI development: RESTful and WebSocket APIs for real-time market data distributionData Engineering & InfrastructureAWS services: EC2, S3, RDS, Kinesis, Lambda, CloudFormation for scalable deploymentsDatabase technologies: Time-series databases (InfluxDB, TimescaleDB), columnar stores (ClickHouse), traditional RDBMSStreaming technologies: Real-time data processing frameworks (Kafka, Kinesis, Apache Spark Streaming)Trading Systems ArchitectureOrder Management Systems: Order routing, execution algorithms, and trade lifecycle managementMarket Data Processing: Tick data ingestion, order book reconstruction, and market microstructure analysisRisk Management: Real-time position monitoring, limit checking, and risk control systemsBacktesting Frameworks: Zipline, Backtrader, QuantConnect, bt, PyAlgoTrade, and custom framework developmentFinancial Markets KnowledgeEquity Markets: Order types, market microstructure, settlement cycles, and trading regulations