Technical Architect (Data Engineering + AI)

Quest Global; Bengaluru; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

Quest Global in Bengaluru, India seeks a seasoned Technical Architect to lead architecture and delivery of an enterprise Data and AI platform. You will craft scalable, governed solutions by integrating data engineering, semantic tech, cloud-native architectures, and Generative AI capabilities.

You will collaborate with stakeholders and engineering teams to define architecture, establish best practices, and drive platform implementation across the full lifecycle.

Qualifications

• Extensive experience in enterprise data and AI architecture.
• Design scalable, governed data platforms and AI-ready solutions.
• Lead technical delivery with AWS and Snowflake.
• Mentor engineering teams and drive best practices.
• Strong communication with stakeholders and clients.

Responsibilities

• Lead the technical design and delivery of data and AI platforms.
• Translate business requirements into scalable technical solutions.
• Provide architectural guidance across project lifecycles.
• Define standards, security, and governance practices.
• Design Knowledge Graphs, Graph RAG, and semantic layers.
• Collaborate with Data/AI/Cloud teams for delivery success.
• Review designs, code, and architecture for quality.

Skills

Enterprise architecture

AWS cloud

Snowflake

Data platforms

Knowledge graphs

Generative AI

REST/GraphQL

Security RBAC/ABAC

Mentoring

Stakeholder mgmt

Tools

Collibra

DBT

OpenSearch

Elasticsearch

MQ

Graph DBs

Vector DBs

Job description

Job Description: Technical Architect (Data Engineering + AI)

We are looking for a 12+ years experienced Technical Architect to lead the architecture and technical delivery of an enterprise-scale Data and AI Platform. The role involves designing scalable, governed, and AI-ready solutions by integrating modern data engineering, semantic technologies, cloud-native architectures, and Generative AI capabilities. The architect will work closely with customer stakeholders and engineering teams to define the solution architecture, establish technical best practices, and drive the successful implementation of the platform.

Key Responsibilities

• Lead the technical design and implementation of enterprise-scale data and AI solutions, ensuring alignment with business objectives and technology standards
• Collaborate with customer stakeholders to understand business requirements and convert them into scalable technical solutions
• Provide technical leadership throughout the project lifecycle, including solution design, estimation, planning, implementation, and deployment
• Define architecture principles, technical standards, and best practices to ensure scalable, secure, and maintainable solutions
• Architect and design highly scalable Knowledge Graphs, Graph RAG solutions, and semantic middleware layers to expose enterprise data as governed Data Products
• Design Natural Language Interfaces, GraphQL, and Streaming Interfaces
• Review solution designs, code, and technical deliverables to ensure quality, performance, and adherence to architectural standards
• Mentor and guide development teams by resolving technical challenges and ensuring best practices
• Evaluate emerging technologies, and tools to recommend the most appropriate solutions
• Work closely with cross-functional teams, including Data Engineers, AI Engineers, Cloud Engineers, DevOps, and QA to ensure successful delivery
• Identify technical risks, recommend mitigation strategies, and proactively address implementation challenges
• Support customer workshops, technical discussions, architecture reviews, and solution demonstrations
• Drive continuous improvement by incorporating lessons learned, optimizing solution design, and promoting reusable architecture patterns

Required Skills

• Strong experience in enterprise solution architecture with modern Data Engineering and AI/GenAI platforms
• Hands-on experience with AWS cloud services and Snowflake
• Experience in designing data platforms, ETL/ELT pipelines, data lakes, data warehouses, and data governance solutions
• Strong understanding of semantic technologies, metadata management, knowledge graphs, ontologies, and data cataloguing concepts
• Experience with Generative AI, LLMs, Graph RAG, Retrieval-Augmented Generation (RAG), vector databases, semantic search, Agentic AI, and Natural Language Interface concepts
• Experience with REST APIs, GraphQL, Streaming Interfaces, microservices, event-driven architecture, and containerized deployments
• Familiarity with Collibra, DBT, OpenSearch/Elasticsearch, MQ, and graph databases and vector databases
• Strong understanding of security, identity management, RBAC/ABAC, and enterprise integration patterns
• Excellent communication, stakeholder management, problem-solving, and technical mentoring skills