Sr Lead Software Engineer - KDB+ / Q

Requirements

  • Formal training or certification on software engineering concepts and advanced applied experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Proficiency in automation and continuous delivery methods
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Development lead experience including requirements capture, task decomposition, time and effort estimation, delivery planning, testing, and user acceptance testing
  • Deep understanding of KDB technology and Q language with at least 7 years professional experience using KDB and at least 2 years as a Lead
  • Deep understanding of KDB+tick design and data organization, including performance implications
  • Practical experience developing and running large datasets and optimizing query performance
  • Practical experience scaling and load-balancing KDB applications
  • Practical experience building resilient and high-availability KDB applications

Nice to Haves

  • Experience with market data venue and vendor data platforms
  • AWS experience
  • Experience with Terraform and Kubernetes managing Production Plants in Public Cloud
  • Experience with additional programming languages such as Python, C, C++, or Java

What You'll Be Doing

  • Executing creative software solutions, design, development, and technical troubleshooting beyond conventional approaches
  • Developing secure, high-quality production code and reviewing/debugging code from others
  • Identifying opportunities to automate remediation of recurring issues to improve operational stability
  • Leading communities of practice across Software Engineering to promote new and leading-edge technologies
  • Contributing to a team culture of diversity, equity, inclusion, and respect
  • Developing core systems and frameworks based on KDB
  • Leading team members through book of work management and improving the team via SDLC, testing, and coding standards
  • Developing scalable real-time processing solutions using agile methodology
  • Partnering with stakeholders to capture requirements and deliver solutions
  • Collaborating with application support teams to maintain and support the platform
AI Summary ✨

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