Senior Architect - Databricks (DE & Gen-AI)

Role Summary

We are looking for a highly experienced Senior Architect to lead the design, architecture, and implementation of enterprise-scale AI-native data platforms on the Databricks Data Intelligence Platform. This role requires a strategic technology leader with deep hands-on expertise in modern Data Engineering, Databricks, and Generative AI. The ideal candidate should be passionate about emerging technologies, capable of rapidly building prototypes and accelerators, mentoring engineering teams, and driving enterprise AI and data transformation initiatives.

Mandatory Skills

AWS Databricks,Databricks Engineer,generative ai,Cloud Data Platforms,Agentic Ai

Role

Key Responsibilities

• Lead the architecture, design, and implementation of enterprise-scale data and AI solutions on the Databricks Data Intelligence Platform.
• Architect modern Lakehouse solutions supporting Data Engineering, AI/BI, Analytics, and GenAI workloads.
• Design scalable, cloud-native data platforms with strong focus on Data Engineering, Data Modeling, Data Quality, Governance, Metadata Management, Security, and Platform Operations.
• Build rapid prototypes, Proof of Concepts (PoCs), Proof of Value (PoVs), and reusable accelerators using Databricks and Generative AI capabilities.
• Design and implement enterprise AI applications leveraging Databricks AI capabilities, Agentic AI, and intelligent analytics.
• Partner with business stakeholders and clients to define technology roadmaps and translate business objectives into scalable technical solutions.
• Collaborate with sales, pre-sales, and account leadership teams to support solutioning, proposals, client presentations, and business development initiatives.

Required Skills & Experience

Databricks & Data Engineering

• Deep hands-on expertise with the Databricks Data Intelligence Platform and modern Lakehouse architecture.
• Strong understanding of Databricks capabilities across Data Engineering, AI/BI, Governance, and AI application development.
• Expert-level Python, PySpark, and SQL with experience building scalable, production-grade applications.
• Strong expertise in:
  • Data Pipeline Design & Automation
  • Data Modeling & Lakehouse Architecture
  • Data Quality & Observability
  • Metadata Management & Data Governance
  • Streaming & Batch Data Processing
  • Performance Optimization

Generative AI & AI Engineering

• Strong hands-on experience building enterprise AI applications on the Databricks Data Intelligence Platform.
• Deep expertise in Databricks AI/BI, including Genie, conversational analytics, and AI-powered business intelligence solutions.
• Hands-on experience designing and implementing Agentic AI solutions using Agent Bricks and the Databricks AI ecosystem.
• Experience building semantic search and enterprise knowledge applications using Databricks Vector Search, enterprise metadata, and governed data assets.
• Strong understanding of the Databricks AI application stack, including Mosaic AI, Agentbricks, Genie Agents, Databricks Apps.
• Knowledge of Retrieval-Augmented Generation (RAG), AI Governance, Evaluation, Prompt Engineering, AI Observability, and responsible AI practices.
• Familiarity with enterprise AI frameworks such as LangChain, LangGraph, LlamaIndex, and Model Context Protocol (MCP) is desirable.

Cloud Platforms

• Experience with Databricks on AWS or GCP.
• Familiarity with Snowflake and modern cloud-native data ecosystems is desirable.

Leadership Competencies

• Strategic thinker with strong architecture and consulting capabilities.
• Dynamic, proactive, and passionate about emerging technologies with the ability to quickly learn and adopt new platform capabilities.
• Strong hands-on practitioner capable of leading architecture while developing prototypes, accelerators, and innovative solutions.
• Demonstrated experience mentoring engineering teams and leading enterprise architecture initiatives.
• Excellent communication, stakeholder management, consulting, and client engagement skills.
• Proven ability to lead technical solutioning, architecture governance, and enterprise transformation programs.

Preferred Qualifications

• 12+ years of experience in Data Engineering, Cloud Data Platforms, or Enterprise Architecture.
• Experience delivering enterprise-scale Databricks implementations and AI-native data platforms.
• Databricks certifications in Data Engineering, Machine Learning, or Generative AI are highly desirable.
• Experience with modern AI-native architectures, semantic layers, knowledge graphs, and metadata-driven data platforms is an added advantage.

Education Qualification

B.tech

Experience

15 to 20 years