Principal Architect – Data Engineering, AI & GCP

Fractal is a strategic AI partner to Fortune 500 companies, aiming to enhance human decision-making through technology. They are seeking a Principal Architect with expertise in Google Cloud Platform and Data Engineering to lead architecture and delivery of AI/ML solutions, ensuring client satisfaction and technical excellence.

Responsibilities:

• 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

Requirements:

• 12+ years in Data Engineering and Cloud-native technologies, with deep GCP expertise
• Hands-on mastery of: BigQuery, Dataflow, Cloud Composer, Vertex AI, Dataproc, Cloud Storage, GCP serverless infrastructure
• Proven delivery of end-to-end Data Engineering, Data Warehousing, or Analytics platforms at scale
• Strong programming skills in Python and/or Java
• Experience with Agile, CI/CD, DevOps, and MLOps pipelines
• Track record leading large, complex, client-facing delivery programs
• Ability to manage cross-functional, cross-geography teams with clarity and accountability
• Prior Google with direct exposure to first party tooling
• Write and optimize queries using PLX to support data analysis and product features
• Proficiency in PLX or similar structured querying languages (e.g. SQL, Dremel/Spanner)
• Docker & Kubernetes experience
• DevOps on GCP
• AWS experience, especially in hybrid cloud contexts
• Google Cloud Professional Cloud Architect Certification