Senior Data Architect/Lead Data Engineer

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.

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 and mentor engineers.

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 and 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.

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.

AI-Native Engineering Skills :

- Claude Code, Cursor, GitHub Copilot, Windsurf, OpenAI, Gemini.

- Agentic frameworks, Model Context Protocol, and prompt engineering.

Leadership and Startup Mindset :

- Startup mindset with independent execution.

- Hands-on across architecture and delivery.

- Ownership, accountability, and customer-first approach.

Education :

- Bachelor's or Master's in a relevant field.

- Relevant cloud/data/AI certifications are a plus.

Why Join Context66 :

- Build a modern Data, AI, and Enterprise Architecture company.

- Work with experienced leaders and solve high-value problems.

- Influence technical strategy and grow into leadership.

- Opportunity to lead enterprise-scale data transformation initiatives.

- High-impact, client-facing role with strong ownership.