Experience: 12+ years of total IT experience, with at least 4+ years acting as a hands-on Data Architect or Enterprise Architect.
Hyperscaler Agnostic: Proven, hands-on architectural experience across multiple major cloud platforms: AWS, Microsoft Azure, and Google Cloud Platform (GCP).
Modern Data Stack: Deep expertise in designing and optimizing solutions on Snowflake and Databricks. Comprehensive understanding of Data Warehousing, Data Lakes, and Data Lakehouse architectures.
Performance Engineering: Master-level proficiency in SQL. Strong ability to optimize complex queries, manage indexing, partition strategies, and compute-warehouse scaling.
AI/GenAI Acumen: Practical experience with Large Language Models (LLMs), Generative AI, and Agentic workflows. Ability to build quick AI POCs (e.g., RAG architectures, prompt engineering, integrating cloud AI services).
Coding Proficiency: Must be genuinely hands-on. Strong proficiency in Python, PySpark, and SQL.
Consulting DNA: Exceptional stakeholder management and communication skills. Ability to push back gracefully, advise senior partners, and thrive in an ambiguous, fast-paced presales environment