Title: Senior Data Architect / Data Engineer

Location: Primary: Hyderabad, India. Other locations: Rest of India, Romania, Colombia, and

Mexico

Employment Type: Full-time, Remote

About Context66

Context66 is a Data, AI, and Enterprise Architecture services company focused on engineering the context that powers AI.

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 / 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/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/engineering.

 Strong architecture plus hands-on engineering.

 Enterprise-scale solution delivery.

 Deep data lifecycle expertise.

 Strong data modeling.

 Experience with ETL, ELT, CDC, APIs, streaming.

 Cloud platforms: Snowflake, Databricks,



AWS, Azure, GCP.

 Data warehouses, lakehouses, mesh, fabric.

 Governance, metadata, lineage, quality.

 Data products and contracts.

 Analytics and AI-ready foundations.

 Excellent communication.

 Explain complex concepts clearly.

AI, Semantic, and Context Engineering Experience

 LLMs, GenAI, intelligent agents.

 RAG, GraphRAG, knowledge graphs, 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, 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/AI certifications are a plus.

Why Join Context66

 Build a contemporary 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.

📌 Data Architect / Lead Data Engineer (India)
🏢 Context66
📍 India