Platform Engineer - Python

Keka Technologies Private Limited; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Zanskar Research in Bangalore is seeking a motivated Software Engineer with hands-on Python experience to join the trading systems team. You will help build high-performance infrastructure for risk calculators, data pipelines, and dashboards, contributing to production-grade systems used across markets.

This role offers rapid growth for early-career engineers, with emphasis on correctness, reliability, and performance.

Qualifications

• 1-2 years of industry or relevant software engineering experience (internships/strong projects considered).
• Proficient in Python and comfortable with Docker for containerisation.
• Exposure to Apache Airflow or similar workflow/orchestration tools.

Responsibilities

• Contribute to core trading system components such as risk calculators, position trackers, and health checkers.
• Build and support data pipelines and workflow automation using Apache Airflow.
• Develop backend services in Python for reliable trading operations.
• Containerise services using Docker and support basic infra/deployment tasks.
• Build and maintain internal dashboards and tooling for operations and monitoring (Grafana).
• Debug and resolve issues in development and production environments.

Skills

Python

Docker

Airflow

Grafana

REST APIs

Linux

Tools

Kafka

Redis

RabbitMQ

Prometheus

ELK

Grafana

Job description

Zanskar Research is a quantitative proprietary trading firm headquartered in Bangalore, operating at the cutting edge of high-frequency and algorithmic trading across Indian and global markets. Our edge is technology - and we intend to keep it that way. Every microsecond counts, and the engineers who build here understand that deeply.

Role Overview

We are seeking a motivated Software Engineer with hands‑on experience in Python to join the trading systems team. The role involves building and maintaining components of high-performance trading infrastructure - including risk calculators, health checkers, data pipelines, and internal dashboards. Work is at the intersection of finance and technology, where correctness, performance, and reliability are non-negotiable. This is a great opportunity for someone early in their career to grow rapidly while working on production-grade systems.

Key Responsibilities

• Contribute to core trading system components such as risk calculators, position trackers, and health checkers, under guidance from senior engineers.
• Build and support data pipelines and workflow automation using Apache Airflow.
• Develop backend services in Python for reliable trading operations.
• Containerise services using Docker and support basic infrastructure/deployment tasks.
• Build and maintain internal dashboards and tooling for operations and monitoring, using tools like Grafana.
• Debug and resolve issues in development and production environments with support from the team.
• Work closely with quants, traders, and senior engineers to understand requirements and implement clean solutions.
• Write clean, testable, and well‑documented code with attention to correctness.

Required Skills & Experience

Core Requirements

• 1-2 years of industry or relevant experience in software engineering (internships/strong projects considered).
• Good proficiency in Python.
• Basic to intermediate experience with Docker for containerisation.
• Exposure to Apache Airflow or similar workflow/orchestration tools (academic or professional).
• Experience building dashboards and monitoring tooling, ideally with Grafana.
• Some full‑stack exposure - ability to build or contribute to simple internal web interfaces (React/Vue/similar + REST APIs).
• Understanding of data structures, basic systems design, and writing reliable code.
• Comfortable working in Linux/Unix environments and with command-line tooling.

Good to Have

• Any prior exposure to fintech, trading systems, or market-related applications.
• Familiarity with messaging systems (Kafka, Redis, RabbitMQ) or time-series databases.
• Basic understanding of networking fundamentals and monitoring/observability tools (Prometheus, ELK) alongside Grafana.