Data Architect/Lead Data Engineer
Listed on 2026-10-08
-
Software Development
Data Engineering, AI Engineer (Applied/Software)
Job Description:
Data Architect / Lead Data Engineer
Location:
Remote,
Role Overview We are seeking an exceptional 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 target architectures, 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.
You will work closely with clients, enterprise architects, AI engineers, product teams, and delivery leaders while contributing to technical standards, delivery methodologies, reusable assets, and engineering culture.
- Design end-to-end enterprise data architectures.
- Define current, transition, and target-state architectures.
- Design modern data platforms, including warehouses, lakes, lake houses, mesh, and 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 solutions, and vector stores.
- Establish metadata, lineage, governance, observability, security, and compliance.
- Support analytics, ML, GenAI, and intelligent-agent initiatives.
- Create reference architectures and engineering standards.
- Conduct architecture reviews and optimization.
- Partner directly with clients and stakeholders.
- Mentor engineers and contribute hands-on to delivery.
- 10--15 years of experience in data architecture and/or data engineering.
- Strong combination of architecture expertise and hands-on engineering.
- Experience delivering enterprise-scale solutions.
- Deep understanding of the end-to-end data lifecycle.
- Strong data modeling expertise.
- Experience with ETL, ELT, CDC, APIs, and streaming.
- Experience with cloud and data platforms such as Snowflake, Databricks, AWS, Azure, and Google Cloud Platform.
- Strong understanding of data warehouses, lake houses, data mesh, and data fabric.
- Experience with data governance, metadata, lineage, and data quality.
- Experience designing data products and data contracts.
- Experience building analytics and AI-ready data foundations.
- Excellent communication and stakeholder-management skills.
- Ability to explain complex technical concepts clearly.
- AI, Semantic & Context Engineering Experience
- Experience with LLMs, GenAI, and intelligent agents.
- RAG, GraphRAG, knowledge graphs, and vector databases.
- Ontologies and semantic modeling.
- Metadata-driven automation.
- AI evaluation and responsible AI practices.
- Enterprise AI integrations.
- AI-enabled data quality and lineage.
- AI-Native Engineering Skills
- Experience with AI-assisted development tools such as Claude Code, Cursor, Git Hub Copilot, Windsurf, OpenAI, and Gemini.
- Familiarity with agentic frameworks.
- Understanding of Model Context Protocol (MCP).
- AI-assisted software and data engineering.
- Prompt engineering and workflow automation.
- Experience implementing AI with human validation and governance.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).