Senior Data Architect/Lead Data Engineer
First seen by Alion on Oct 26, 2026.
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.
Skills
Data Engineering, Data Modeling, Data Governance, AWS, Azure, Databricks, ETL, Data Architect, Data Warehousing, Snowflake DB