Senior Engineering Lead Analyst-5

• Architect and implement scalable solutions using Snowflake and Databricks on AWS and Azure

Design and implement AI and Gen AI solution for data value chain

• Design data integration pipelines (batch, real-time, big data) and analytics platforms

• Define and implement data governance, quality, meta data, and lineage frameworks and should be able to leverage GenAI capabilities.

• Act as a trusted advisor to senior business and IT stakeholders

Architect Agentic AI ecosystems using LLMs, vector databases, and orchestration frameworks (LangChain, AutoGen, CrewAI).

• Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.

• Design Agent-to-Agent (A2A) communication protocols for collaborative multi-agent workflows.

• Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.

Senior Cloud Data & AI Architect Must Have Technical/Functional Skills

• Architect enterprise data platforms for data lake, Lakehouse, streaming systems.

• Design data integration and data pipeline patterns

• Should be able to evaluate new technologies and run proof of concepts.

• Should be able to set data and AI strategy for data organization.

• Established data Quality, lineage and metadata standards

• Ensured compliance with privacy, security and regulation

• Drives adoption of responsible AI frameworks

• Created architectural guardrails

• Drive consensus on standards (eg data contracts, lineage) across different data organizations

• Reviews design and elevate architectural thinking across teams

• Creates reusable patterns, templates and reference architectures

• Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation

• Design and implement AI and Gen AI solution for data value chain

• Strong experience with LLMs, prompt engineering, and agent frameworks (LangChain, AutoGen, CrewAI).

• Deep understanding of MCPs, ReAct, Tree of Thought, and AutoGPT-style reasoning.

• Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate).

• Experience with A2A orchestration, agent memory strategies, and tool calling.

• Strong grasp of enterprise architecture, data governance, and security protocols.

• Experience with cloud platforms (Azure, AWS, GCP) and MLOps pipelines.

• Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation

• Implement retrieval-augmented generation (RAG) pipelines with memory, context management, and tool usage.

• Define Model Context Protocol (MCPs) to chain reasoning, retrieval, and action models.

• Hands-on with Python, OpenAI APIs, Anthropic Claude, Vector DBs (FAISS, Pinecone, Weaviate)., * 15-20 years of experience in data architecture, data engineering, and analytics platforms

• Strong consulting experience in large BFSI transformation programs

• Hands-on expertise with Snowflake and Databricks (Lakehouse architecture)

• Design and implement AI and Gen AI solution for data value chain

• Very strong understanding and experience on Data products, data mesh and Medallion Architecture implementation

• Experience with cloud data services in aws,azure,gcp

• Strong background in data integration, reporting, and big data ecosystems

• Experience working in regulated environments with data governance and compliance requirements

• Excellent stakeholder communication and leadership skills