Lead Software Engineer

Mastercard Mastercard · Fintech · Pune, Mahārāshtra, India · Engineering

Lead Software Engineer at Mastercard's Artificial Intelligence & Decision Product Enablement (AI & DPE) team, focusing on real-time streaming analytics for intelligent decision-based products to support Cyber Intelligence and Fraud Prevention. The role involves owning complex problems, writing and reviewing code, defining solutions, driving prioritization, automating delivery, ensuring seamless integration, and promoting best practices.

What you'd actually do

  1. Own complex problems having dependency across services and facilitate cross-functional team interactions to drive resolution
  2. Write code to build and enhance applications/services and promote code-reviews, code scanning, and other standard development practices to deliver high-quality artifacts to production.
  3. Define, design, and develop procedures and solutions at a service level to meet the business requirements/enhancements
  4. Drive prioritization decisions and trade-offs in working with product partners
  5. Identify opportunities and build roadmaps to enhance primary service/function

Skills

Required

  • Java
  • Python
  • GO
  • JavaScript
  • secure coding standards
  • OWASP
  • CWE
  • SEI CERT
  • Spring Boot
  • Angular
  • operating systems internals
  • debugging
  • troubleshooting
  • documentation
  • coding guidelines
  • design patterns
  • code review
  • technical debt
  • operational issues
  • system architecture
  • platform and infrastructure capacity planning
  • customer journeys
  • Mean time to mitigate (MTTM)
  • high availability
  • deployment simplification
  • release workflows and pipelines
  • CI/CD
  • Jenkins
  • Bamboo
  • AWS/Azure pipelines
  • XL Release
  • code vulnerability scanning
  • software composition analysis
  • Sonar
  • Checkmarx
  • Nexus
  • JFrog XRay
  • Veracode
  • test runs definition and reporting
  • performance tests

What the JD emphasized

  • secure code
  • secure coding standards
  • vulnerabilities
  • high availability (99.95%)