KDB Lead Developer

EPAM Systems

Coimbatore District

On-site

INR 4,200,000 - 6,400,000

Full time

14 days+

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Job summary

EPAM Systems is seeking a KDB Lead Developer to join our front-office technology team in India, focusing on time-series analytics, low-latency data processing and market data analysis for trading strategies.

You will design, develop and optimize KDB+/q-based platforms, collaborate with quants, traders and technologists, and ensure robust performance, reliability and scalable data pipelines across real-time analytics and dashboards.

Qualifications

  • 8-12 years of professional experience developing with KDB+/q in a financial or trading environment.
  • Solid understanding of market data such as Level 1/2, order book dynamics, trades and quotes.
  • Familiarity with algorithmic trading concepts including VWAP, TWAP, arrival price, slippage and market impact.
  • Strong background in time-series data structures, analytics and performance tuning.
  • Proficiency in integrating KDB with Python, Java or Kafka and REST APIs.
  • Excellent problem-solving skills and a proactive detail-oriented mindset.
  • Effective communicator able to collaborate across business and technical teams.

Responsibilities

  • Design, develop and maintain KDB+/q-based data capture, analytics and visualization platforms
  • Optimize time-series data queries and real-time analytics pipelines for performance and scalability
  • Work with quantitative researchers and algo developers to deliver high-performance metrics and diagnostics tools
  • Integrate KDB systems with market data feeds, order management systems and trading platforms
  • Build dashboards and monitoring tools for algorithm performance and market behavior
  • Maintain large-scale tick data stores including data hygiene, normalization and lifecycle management
  • Collaborate with DevOps and Infrastructure teams to ensure system reliability and uptime

Skills

KDB+/Q
Low-latency
Time-series analytics
Python
Java
Kafka
REST APIs

Tools

Dash
Grafana

Job description

We are looking for a KDB Lead Developer to join our front-office technology team, supporting algorithmic trading and high-frequency trading (HFT) initiatives.

This role focuses on developing and optimizing time-series analytics systems, collaborating with quants, traders and technologists to deliver robust, low-latency solutions for market data analysis and strategy performance.

Responsibilities
  • Design, develop and maintain KDB+/q-based data capture, analytics and visualization platforms
  • Optimize time-series data queries and real-time analytics pipelines for performance and scalability
  • Work with quantitative researchers and algo developers to deliver high-performance metrics and diagnostics tools
  • Integrate KDB systems with market data feeds, order management systems and trading platforms
  • Build dashboards and monitoring tools for algorithm performance and market behavior
  • Maintain large-scale tick data stores including data hygiene, normalization and lifecycle management
  • Collaborate with DevOps and Infrastructure teams to ensure system reliability and uptime
Requirements
  • 8-12 years of professional experience developing with KDB+/q in a financial or trading environment
  • Solid understanding of market data such as Level 1/2, order book dynamics, trades and quotes
  • Familiarity with algorithmic trading concepts including VWAP, TWAP, arrival price, slippage and market impact
  • Strong background in time-series data structures, analytics and performance tuning
  • Proficiency in integrating KDB with Python, Java or Kafka and REST APIs
  • Excellent problem-solving skills and a proactive detail-oriented mindset
  • Effective communicator able to collaborate across business and technical teams
Nice to have
  • Experience with real-time market data capture and event processing
  • Knowledge of equities, FX, futures or fixed income trading workflows
  • Familiarity with data visualization tools such as Dash, Grafana or custom q dashboards
  • Experience working in low-latency high-throughput environments
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