Principal Software Engineer Architect

The Impact of a Principal Software Engineer: The Principal Software Engineer - Analytics will serve as an architect and visionary leader, responsible for the overall design, strategy, and implementation of our analytics and data applications. This role will encompass all aspects of data engineering, analytics applications, and infrastructure, driving innovation, scalability, and performance across the entire ecosystem. Key Responsibilities: - Architect the overall vision and strategy for the analytics and data applications, ensuring alignment with business goals and scalability for future growth. - Lead the architecture and development of advanced analytics tools and applications, including sophisticated user & agentic interfaces for data visualization and interactive experiences. - Establish and enforce best practices for data transport, microservice orchestration, platform monitoring, and alerting across all data and analytics initiatives. - Provide technical leadership and mentorship to engineering teams, guiding architectural decisions and ensuring code quality and performance optimization. - Drive innovation by evaluating and implementing cutting-edge technologies in big data, cloud computing, AI/ML, and API development. - Ensure stringent data security and governance across all AWS regions and data assets. - Collaborate with cross-functional teams, including product, design, and engineering, to translate complex business requirements into robust technical solutions. Qualifications: - 15+ years of Software Engineering experience within an enterprise grade environment, with significant leadership and architectural roles. - Hands-on application building using tech stack: Java, .Net, or Ruby (Rails). - Experience in building AI Agents, NLP is preferred. - Advanced degree in a quantitative discipline or equivalent practical experience. - Extensive experience in designing and developing API-driven services (REST, GraphQL), knowledge graphs and microservice architectures. - Strong understanding and application of AI/ML techniques for data classification, harmonization, and predictive analytics. - Demonstrated ability to mentor and guide engineering teams, providing technical leadership and strategic direction. - Highly skilled in analytical problem-solving, root cause analysis, and optimization of complex data processes across structured and unstructured datasets. - Exceptional communication and collaboration skills, with the ability to effectively communicate complex technical concepts to diverse audiences.