Senior Technical Architect- Customer Systems

In this role, you will be involved in end to end cycle of design, development and deployment of core services for mission critical customer facing applications. Our applications rely on a complex ecosystem that is supported by multiple engineering teams. You will be responsible for understanding the needs and changes across the ecosystem and build a strategic roadmap. To ensure alignment of your roadmap with the various engineering team, you will partner with respective product owners to prioritize trade-offs, clarify requirements, and drive towards product goals. You will define technical solutions for business problems, define system interfaces and data flow across systems, write technical user stories, and advocate for end-user and business needs. You will also facilitate effective communication between business and engineering teams to get issues resolved. You will have extensive technical conversations with engineers and non-technical professionals, and will be required to present in front of senior leaders. Minimum Qualifications Exceptional software engineering background with an outstanding body of work demonstrating experience in software development, solution architecture 13+ years of Industry and hands on experience in architecting and developing event-based, distributed, highly available systems. Deep knowledge of developing and managing enterprise-level technology at a global scale Experienced with Micro-services, CI/CD Hands-on with one or more cloud platforms and managed services Hands-on Expertise in Java, Springboot, Kubernetes, Docker, Kafka, Object Oriented Programming Experience in working with a global team across different timezones. B.Tech. degree in computer science or equivalent field Preferred Qualifications Excellent communication skills and attention to detail for documenting and reviewing designs Excellent problem-solving and analytical skills Excellent leadership and influencing skills Effective presentation, oral, and written business communication skills with various audiences and levels Familiarity with machine learning algorithms and techniques such as regression, classification, clustering, and natural language processing.