Solution Architect

DAAS Labs; Gurugram District; On-site; INR 2,800,000 - 4,000,000; Full time

Job summary

DAAS Labs seeks a seasoned Cloud Data Architect to lead client engagements and design scalable data platforms on AWS, Snowflake, and Databricks. You will shape technical solutions for large enterprises and guide teams across multiple disciplines.

You will drive pre-sales efforts and governance of AI/data projects, while mentoring engineers and maintaining strong executive communications with clients.

Qualifications

• 8-15 years of overall experience in client-facing solution/technical architecture roles.
• Experience delivering enterprise data platforms on AWS, Snowflake, and/or Databricks.
• Hands-on exposure to GenAI: LangChain, LangGraph, RAG, agents, knowledge graphs, and AI guardrails.
• Experience with AWS AI/ML services: Bedrock, SageMaker, Bedrock Agents, and core cloud services (ECS/EKS, Lambda, API Gateway, Step Functions, EventBridge, DynamoDB).
• Strong data engineering fundamentals — Spark, Python, SQL/PL-SQL, lakehouse/data mesh patterns.
• Demonstrated experience in pre-sales: RFP/RFI responses, effort estimation, solution budgeting, POV/POC development.
• Track record of driving measurable business value through architected AI or data solutions.
• Experience onboarding 1,000+ users onto governed data platforms.
• Familiarity with regulated environments (Life Sciences/GxP or similar) is a strong plus.
• Experience building or governing conversational AI/chatbot ecosystems is a plus.
• Strong stakeholder management and executive communication skills; ability to influence at leadership levels.
• Experience leading and mentoring cross-functional, multi-cultural engineering teams.

Responsibilities

• Lead architecture discussions with clients and translate business needs into scalable data and AI solutions.
• Design and govern enterprise data platforms on AWS, Snowflake, and Databricks for large-scale deployments.
• Drive pre-sales activities including RFPs/RFIs, budgeting, and POV/POC development.
• Mentor cross-functional teams and promote best practices in data engineering and GenAI implementations.

Skills

Enterprise data platforms

AWS

Snowflake

Databricks

GenAI technologies

LangChain

LangGraph

Spark

Python

SQL

Pre-sales

User onboarding

Regulated environments

Stakeholder mgmt

Leadership

Education

Bachelor's degree

Master's preferred

Tools

Bedrock

SageMaker

LangChain

LangGraph

DynamoDB

ECS/EKS

API Gateway

Step Functions

EventBridge

Job description

Requirements

• 8-15 years of overall experience, with a significant portion in client-facing solution/technical architecture roles.
• Proven experience architecting and delivering enterprise data platforms on AWS, Snowflake, and/or Databricks.
• Strong hands-on exposure to GenAI technologies: LLM orchestration (LangChain, LangGraph or equivalent), RAG, Agentic AI/Deep Agents, knowledge graphs, and AI guardrails.
• Experience with AWS AI/ML services such as Bedrock, SageMaker, Bedrock Agents, along with core cloud services (ECS/EKS, Lambda, API Gateway, Step Functions, EventBridge, DynamoDB).
• Solid understanding of data engineering fundamentals — Apache Spark, Python, SQL/PL-SQL, and modern lakehouse/data mesh architecture patterns.
• Demonstrated experience in pre-sales: RFP/RFI responses, effort estimation, solution budgeting, and POV/POC development.
• Track record of driving measurable business value/revenue through architected AI or data solutions.
• Experience with self-service analytics enablement and onboarding large user bases (1,000+ users) onto governed data platforms.
• Familiarity with regulated industry environments (Life Sciences/GxP or similar) is a strong plus.
• Experience building or governing conversational AI/chatbot ecosystems is a plus.
• Strong stakeholder management and executive communication skills; ability to influence at leadership levels.
• Experience leading and mentoring cross-functional, multi-cultural engineering teams.

Preferred Certifications

• AWS Certified Solutions Architect / Data Engineer / AI Practitioner / Generative AI (any combination).
• Microsoft Azure Fundamentals (or equivalent multi-cloud exposure).
• Agile / IBM Design Thinking or equivalent delivery methodology certifications.
• Bachelor's degree in Computer Science, Engineering, or a related technical field (Master's preferred but not mandatory).