Principal Engineer – Data Platforms, Azure & GenAI

Role Summary: We are looking for a Principal Engineer who combines deep technical mastery across data platforms and software systems with a forward-looking vision for AI adoption. This is a technical leadership role for an individual who thrives on solving complex, large-scale data problems, designs and builds robust software systems, influences architecture and engineering practices across the organization, and champions the responsible adoption of Generative & Agentic AI. You will work extensively within the data and cloud ecosystem, partnering with senior leaders and stakeholders across the business, while mentoring engineers and setting the standard for engineering excellence, without direct people-management responsibilities! What You'll Do Architect, Design and drive/implement engineering deliverables across complex, high-scale data landscapes spanning multiple domains and platforms. Design, build, and optimize batch and streaming data pipelines in On Prem and in Azure leveraging Azure services Own data modeling and engineering strategy for analytics, ensuring data is well-structured, discoverable, and trustworthy across the data estate. Establish best practices for data quality, observability, and pipeline reliability, leveraging Azure services. Design and build microservices and backend APIs, choosing the right compute model for each workload. Apply sound system design and architecture patterns to ensure systems are scalable, maintainable, resilient, event-driven and asynchronous. Champion strong CI/CD and DevOps practices in both On Prem and Azure Act as a hands-on contributor — writing code, reviewing designs, and solving the hardest technical problems alongside the team. Leadership & Influence Partner directly with senior leaders and multi-functional stakeholders to translate business priorities into scalable technical solutions. Evangelize and drive adoption of Generative & Agentic AI across engineering teams Provide hands-on technical leadership, mentorship, and coaching to engineers at all levels, elevating engineering standards organization-wide. Champion a culture of innovation, experimentation, and continuous improvement in engineering practices. Mandatory Skills: ·       15+ years of progressive experience in data and software engineering, with demonstrated ownership of large, complex data landscapes. ·       Deep data engineering expertise — pipeline design (batch & streaming, ETL/ELT), data modeling, and warehousing for large-scale analytics. ·       Strong expertise in Database and Data management, advanced expertise in SQL and relational/analytical data modeling for large-scale systems. ·       Strong proficiency in at least one programming language — Python or Java preferred — with a track record of production-grade code delivery. ·       Proven experience designing and building microservices architectures, including system design and CI/CD practices.