You will work with other software engineers, data scientists, ML engineers, designers, project managers and business subject matter experts on interdisciplinary projects to enable business ambitions with data & analytics.
You will: Collaborate cross-functionally with business stakeholders, software engineers, data scientists, data engineers, and internal teams to understand business and operational needs and translate them into reliable, scalable, and reusable technical solutions; autonomously investigate, troubleshoot, and resolve complex issues across the full application stack, while maintaining platform stability, reliability, and availability; diagnose technical issues through structured root-cause analysis and deliver robust code fixes, translating operational learnings into engineering improvements that reduce technical debt and prevent issue recurrence.
You will also design, evolve, and maintain observability capabilities across monitoring, logging, and tracing to provide visibility into application health, identify performance and reliability issues, and support effective production troubleshooting; own the end-to-end resolution of production issues, from initial triage and root-cause analysis through code fixes and production releases, while enhancing CI/CD pipelines and conducting rigorous post-deployment validation to ensure reliable, non-disruptive releases; and leverage Generative AI and agentic engineering approaches to enhance software development practices, automate engineering workflows, and improve the design, development, testing, and maintenance of software solutions.