Senior Data Architect - Data Engineering & AI
First seen by Alion on Oct 26, 2026.
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.
Skills
Data Modeling, Data Governance, Data Analytics, Artificial Intelligence, Data Management, Data Architect