Data & AI Engineering Leader

You should have around 18-20 years of total experience, out of which 8-10 years should be focused on full-stack engineering. You should have progressed from an individual contributor role to leading large engineering teams on a global scale. Your track record should demonstrate your ability to build scalable software products and successfully manage consulting engagements. Experience in overseeing multiple programs across distributed teams is crucial. A strong background in Software Engineering, Digital Solutions, and Digital Transformation is a must. You should possess expertise in software development methodologies, enterprise-grade systems, and customer-specific solutions. Leading large global software engineering teams will be a key responsibility. You should have a solid understanding of distributed systems, cloud-native architectures, and real-time analytics. Proficiency in Data Structures, Algorithms, and the capability to contribute code for Proof of Concepts are essential. Hands-on experience with tools such as Databricks, Snowflake, RDBMS, NoSQL, and Python is required. Familiarity with Cloud ETL pipelines, data modeling, and data governance tools is preferred. Additionally, you should have a minimum of 1-2 years of experience in AI/GenAI/Agentic AI frameworks and related use cases.,