Verified Job
Engineering - Architecture
Engineering Lead – Quant Infrastructure
Engineering - Architecture
#27547
Remote / WFH
Fintel Research Labs Pvt Ltd
Job Description
Company Description Fintel Research Labs Pvt Ltd specializes in quantitative research, statistical analysis, market microstructure, and machine learning applications in finance. Our team, founded by experienced professionals in technology and capital markets, analyzes extensive financial market data to uncover patterns in liquidity, volatility, and participant behavior. Central to our research is PRISM, a sophisticated analytical framework designed to study financial markets using multilayered data and statistical tools.
We are committed to leveraging computational expertise to deliver cutting-edge insights in capital markets analysis.
Engineering
Lead – Quant Infrastructure Pune 6 Years – 8 Years Experience About the Role Fintel Research Labs (FRL) is building a research-driven, multi-engine trading system (PRISM) across equities, derivatives, and cross-asset markets. We focus on systematic trading, data infrastructure, and robust execution systems at institutional scale. We’re hiring a hands-on Platform Engineering Lead to own backend architecture, data systems, and end-to-end integration of our investment platform.
What You’ll Do Architecture & Platform Ownership - Own overall platform architecture across data ingestion, research, execution, risk, monitoring, and analytics systems
• Design scalable, fault-tolerant, event-driven architectures for low-latency trading workflows
• Review and optimize system architecture, infrastructure choices, and hosting strategies across cloud and on-prem environments
• Define engineering standards for scalability, reliability, observability, and security Data Engineering / Data Governance - Design and maintain time-series data architecture for market, trade, and analytics datasets
• Own data quality processes including validation, reconciliation, lineage, completeness checks, and issue remediation
• Troubleshoot production data issues including missing ticks, feed breaks, latency spikes, pipeline failures, and historical inconsistencies
• Establish data storage, partitioning, retention, backup, and recovery strategies Production / Reliability - Drive monitoring, logging, observability, and alerting frameworks
• Lead root-cause analysis (RCA) and incident resolution for production issues
• Improve system performance, latency, resiliency, and operational reliability Leadership - Lead system engineering team
• Drive architecture reviews, code reviews, hiring, and technical roadmap planning
• Coordinate across quant research, engineering, and product teams
• Design scalable backend systems for strategy, execution, and risk
• Build and manage data pipelines (real-time + historical)
• Own end-to-end system flow (signal → execution → monitoring) Mandatory Skills - 6–8 years in backend / data engineering - Time-series databases / architectures, ETL / ELT design, Data lineage and reconciliation
• Strong Python, C++ and SQL language experience
• Event-driven systems architecture, disaster recovery, microservices and distributed architecture patterns
• System design and performance optimization
• PostgreSQL, Redis, Kafka, Docker, Kubernetes, Git/GitHub, CI/CD pipelines
• Experience building end-to-end systems
• Solid understanding of:
• Data modeling (time-series preferred)
• API integration
• Distributed systems
• Overall back-end systems architecture
• Hands-on experience with AWS / Azure and on-premise servers Preferred skills:
• Experience designing market data platforms, execution systems, OMS/EMS, or quantitative infrastructure
• Exposure to time-series databases and financial market data pipelines
• Experience troubleshooting production trading systems and real-time data workflows Education - B.Tech / M.Tech / Bachelors in Computer Science, Engineering, or related field
We are committed to leveraging computational expertise to deliver cutting-edge insights in capital markets analysis.
Engineering
Lead – Quant Infrastructure Pune 6 Years – 8 Years Experience About the Role Fintel Research Labs (FRL) is building a research-driven, multi-engine trading system (PRISM) across equities, derivatives, and cross-asset markets. We focus on systematic trading, data infrastructure, and robust execution systems at institutional scale. We’re hiring a hands-on Platform Engineering Lead to own backend architecture, data systems, and end-to-end integration of our investment platform.
What You’ll Do Architecture & Platform Ownership - Own overall platform architecture across data ingestion, research, execution, risk, monitoring, and analytics systems
• Design scalable, fault-tolerant, event-driven architectures for low-latency trading workflows
• Review and optimize system architecture, infrastructure choices, and hosting strategies across cloud and on-prem environments
• Define engineering standards for scalability, reliability, observability, and security Data Engineering / Data Governance - Design and maintain time-series data architecture for market, trade, and analytics datasets
• Own data quality processes including validation, reconciliation, lineage, completeness checks, and issue remediation
• Troubleshoot production data issues including missing ticks, feed breaks, latency spikes, pipeline failures, and historical inconsistencies
• Establish data storage, partitioning, retention, backup, and recovery strategies Production / Reliability - Drive monitoring, logging, observability, and alerting frameworks
• Lead root-cause analysis (RCA) and incident resolution for production issues
• Improve system performance, latency, resiliency, and operational reliability Leadership - Lead system engineering team
• Drive architecture reviews, code reviews, hiring, and technical roadmap planning
• Coordinate across quant research, engineering, and product teams
• Design scalable backend systems for strategy, execution, and risk
• Build and manage data pipelines (real-time + historical)
• Own end-to-end system flow (signal → execution → monitoring) Mandatory Skills - 6–8 years in backend / data engineering - Time-series databases / architectures, ETL / ELT design, Data lineage and reconciliation
• Strong Python, C++ and SQL language experience
• Event-driven systems architecture, disaster recovery, microservices and distributed architecture patterns
• System design and performance optimization
• PostgreSQL, Redis, Kafka, Docker, Kubernetes, Git/GitHub, CI/CD pipelines
• Experience building end-to-end systems
• Solid understanding of:
• Data modeling (time-series preferred)
• API integration
• Distributed systems
• Overall back-end systems architecture
• Hands-on experience with AWS / Azure and on-premise servers Preferred skills:
• Experience designing market data platforms, execution systems, OMS/EMS, or quantitative infrastructure
• Exposure to time-series databases and financial market data pipelines
• Experience troubleshooting production trading systems and real-time data workflows Education - B.Tech / M.Tech / Bachelors in Computer Science, Engineering, or related field
