• Define short- and long-term technology vision for clients, evaluating their current landscape and charting a path forward.
• Lead end-to-end architecture for Data Engineering, Data Warehousing, and AI/ML solutions on GCP.
• Design scalable, secure, future-proof solutions using GCP-native services BigQuery, Dataflow, Cloud Composer, Vertex AI, Dataproc, Cloud Storage, and more.
• Build foundational architectures: microservices, event-driven systems, event streaming, and online ML systems.
• Champion data governance, data management best practices, and platform maintainability.
• Act as Delivery Lead on large-scale programs owning timelines, quality, risk, and client satisfaction end to end.
• Drive program governance across workstreams, keeping cross-functional and cross-geography teams aligned.
• Step in hands-on during critical delivery phases architecture validation, performance tuning, production issue resolution.
• Bridge the gap between architecture decisions and execution realities, ensuring long-term scalability is never sacrificed for short-term speed.
• Mentor delivery teams, instilling strong engineering practices, accountability, and a culture of continuous improvement.
• Become a trusted thought partner to senior client leaders understanding their pain points and translating them into actionable technical strategies.
• Proactively identify client needs and align them with innovative, business-impacting solutions.
• Communicate complex technical concepts clearly across executive, business, and engineering audiences.
• Build lasting relationships with senior stakeholders and cross-functional teams.
• Contribute to best practices, reference architectures, and technical content that elevate the broader practice.
• Collaborate with data engineers and data scientists to co-develop architecture that serves both analytical and operational needs.