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.