Principal Architect – Data Platforms & Architecture (SME)

Role Overview

The Principal Architect in Delivery leads architecture for large Azure programs that span applications, platforms, and data. You connect business goals to cloud modernization roadmaps, define architecture frameworks, and guide multi-team execution.

At this level, you act as an organization-wide technical leader. You set technical direction across practices, orchestrate cross-team discovery, keep designs aligned across multiple teams, and turn successful patterns into reusable models. You promote strong engineering, automation, and AI-assisted practices, mentor Senior Architects and Delivery Architects, and help build an inclusive, continuously improving engineering culture while supporting clear investment and modernization decisions for 3Cloud and our clients.

Responsibilities

• Lead architecture and technical strategy for large Azure programs and portfolios so solutions meet client goals for value, security, scalability, reliability, performance, and cost.
• Define modernization blueprints and reference architectures across applications, platforms, and data, including system and subsystem designs, patterns, and standards that simplify delivery and operations over time.
• Translate business and product strategy into cloud architecture roadmaps and execution plans that drive measurable outcomes and adapt based on production feedback and telemetry.
• Guide major architecture decisions across programs, promote shared design standards and reusable models, and resolve high-impact technical trade-offs.
• Work across teams to connect solutions into cohesive end-to-end architectures with clear ownership boundaries and integration contracts.
• Provide architectural oversight during delivery through design reviews, forums, and governance, keeping cross-cutting concerns (security, performance, resilience, availability, compliance, observability, and cost) aligned across teams.
• Promote modular design, clear boundaries, testability, CI/CD, and observability so non-functional requirements are treated as first-class and systems remain reliable and maintainable.
• Use AI tools to accelerate discovery, design, code, tests, documentation, and analysis, and scale successful practices so teams adopt them consistently.
• Own architectural standards for lakehouse, streaming, and AI-enabled data platforms.
• Guide large-scale Databricks implementations, including multi-region deployments.
• Expert knowledge of Data Management, Business Intelligence and Analytics concepts including:
• Data Movement (ETL/ELT).
• Data Warehousing (Designing and Implementing, Azure SQL, Synapse).
• Azure Storage Technologies (Data Lake, Blob Storage).
• Data Governance (including Data Quality and Profiling, Master Data Management).