Senior Data Architect - Data Engineering & AI

Senior Data Architect: Location: Primary: Hyderabad, India. Other locations: Rest of India. Employment Type: Full-time, Remote. We help enterprises transform fragmented data, systems, documents, and business knowledge into trusted, governed, reusable, and AI-ready enterprise context. Our work spans modern data foundations, enterprise data architecture, integration, semantic layers, knowledge graphs, GraphRAG, ontologies, metadata, intelligent automation, and production-grade AI systems. We believe AI does not scale on data alone. It scales on trusted context. Context66 combines deep architecture expertise, hands-on engineering, AI-native delivery, and reusable accelerators to help organizations simplify complexity, modernize platforms, improve data trust, and move AI from experimentation into measurable enterprise outcomes. Role Overview: We are seeking an exceptional Senior Data Architect or Lead Data Engineer who combines deep architectural thinking with strong hands-on engineering capabilities. This is not a documentation-only architecture role. The ideal candidate can define the target architecture, make critical technology decisions, design reusable patterns, and work directly with engineering teams to build and deliver production-grade solutions. You will help design and implement modern enterprise data platforms, integration frameworks, governed data products, semantic layers, knowledge graphs, GraphRAG solutions, and AI-ready data foundations. Work closely with clients, enterprise architects, AI engineers, product teams, and delivery leaders. Help shape technical standards, delivery methodologies, reusable assets, and engineering culture. Key Responsibilities: - Design end-to-end enterprise data architectures. - Define current, transition, and target-state architectures. - Design modern data platforms (warehouses, lakes, lakehouses, mesh, fabric). - Build scalable ingestion, integration, transformation, orchestration, and activation pipelines. - Define ETL, ELT, API, CDC, and streaming integration patterns. - Design governed data products. - Develop conceptual, logical, physical, canonical, and semantic data models. - Build semantic layers, ontologies, knowledge graphs, GraphRAG, and vector stores. - Establish metadata, lineage, governance, observability, security, and compliance. - Support analytics, ML, GenAI, and intelligent agents. - Create reference architectures and engineering standards. - Perform architecture reviews and optimization. - Partner with clients. - Mentor engineers. - Contribute hands-on to delivery. Required Experience and Skills: - 10 - 15+ years in data architecture or engineering. - Strong architecture plus hands-on engineering. - Enterprise-scale solution delivery. - Deep data lifecycle expertise. - Strong data modeling. - Experience with ETL, ELT, CDC, APIs, and streaming. - Cloud platforms: Snowflake, Databricks, AWS, Azure, GCP. - Data warehouses, lakehouses, mesh, and fabric. - Governance, metadata, lineage, and quality. - Data products and contracts. - Analytics and AI-ready foundations. - Excellent communication. - Explain complex concepts clearly. AI, Semantic, and Context Engineering Experience: - LLMs, GenAI, and intelligent agents. - RAG, GraphRAG, knowledge graphs, and vector databases. - Ontologies and semantic modeling. - Metadata-driven automation. - AI evaluation and responsible AI. - Enterprise AI integrations. - AI-enabled data quality and lineage. AI-Native Engineering Skills: - Claude Code, Cursor, GitHub Copilot, Windsurf, OpenAI, and Gemini. - Agentic frameworks. - Model Context Protocol. - AI-assisted engineering. - Prompt engineering and workflow automation. - AI with human validation and governance. Leadership and Startup Mindset: - Startup mindset. - Independent execution. - Hands-on across architecture and delivery. - Ownership and accountability. - Customer-first. - Challenge assumptions. - Continuous learning. - Mentor others. - Help build the company. Education: - Bachelor's or Master's in a relevant field. - Relevant cloud, data, or AI certifications are a plus. Why Join Context66: - Build a modern Data, AI, and Enterprise Architecture company. - Work with experienced leaders. - Solve high-value problems. - Build AI and data platforms. - Influence technical strategy. - Grow into leadership. - We are looking for builders who combine architecture depth, engineering discipline, curiosity, and a strong commitment to customer outcomes. Why Join Us: - Opportunity to lead enterprise-scale data transformation initiatives. - Work across diverse industries and complex data ecosystems. - Drive both architecture strategy and hands-on implementation. - High-impact, client-facing role with strong ownership.