Senior Cloud Data & AI Architect

Tata Consultancy Services; Dallas (TX); On-site; USD 150,000 - 175,000; Full time

Job summary

Tata Consultancy Services in Dallas, TX, is seeking a senior data architecture leader to design and modernize enterprise data platforms, including data lake, lakehouse and AI-enabled pipelines. Lead data governance, quality, lineage and security, and drive scalable Snowflake and Databricks solutions on AWS/Azure.

Guide GenAI and RAG initiatives across banking and insurance clients while ensuring regulatory compliance.

Qualifications

• 15–20 years of experience in data architecture, data engineering, and analytics platforms.
• Strong consulting experience in large BFSI transformation programs.
• Hands-on experience with Snowflake and Databricks (Lakehouse architecture).
• Experience with cloud data services in AWS/Azure/GCP.
• Experience implementing GenAI in data value chains.

Responsibilities

• Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients.
• Architect and implement scalable data solutions using Snowflake and Databricks on AWS/Azure.
• Drive data governance, quality, metadata, and lineage frameworks including GenAI capabilities.
• Define architectures and guardrails for data contracts, lineage, and security.

Skills

Data architecture

Cloud platforms

Snowflake

Databricks

AI/GenAI

Job description

Job Description

• 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).

Roles & Responsibilities

• Lead enterprise data platform modernization from on-prem to cloud for banking and insurance clients.
• 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.

Generic Managerial Skills, If any

• 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

Salary Range- $150,000-$175,000 a year