Senior Data Architect / Lead Data Engineer (10+ Years)

Company: Company

*Job description*
Title: Senior Data Architect / Data Engineer
Location: Remote
Employment Type: Full-time, Remote
*About Context66*
Context66 is a Data, AI, and Enterprise Architecture services company focused on engineering the context that powers AI.
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 / 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. You will work closely with clients, enterprise architects, AI engineers, product teams, and delivery leaders to translate complex business needs into scalable, secure, and maintainable solutions.
This is an early, high-impact role within the Context66 CTO organization. The successful candidate will help shape our technical standards, delivery methodologies, reusable assets, and engineering culture.
*Key Responsibilities*
* Design end-to-end enterprise data architectures across structured, unstructured, streaming, batch, and event-driven data
* Define current-state, transition-state, and target-state architectures aligned with business outcomes
* Design and implement modern data platforms, including data warehouses, data lakes, lakehouses, data mesh, data fabric, and federated data architectures
* Build scalable data ingestion, integration, transformation, orchestration, and activation pipelines
* Define integration patterns across ETL, ELT, APIs, CDC, messaging, streaming, micro-batch, virtualization, and zero-copy architectures
* Design reusable, governed data products with clear ownership, contracts, SLAs, quality expectations, and lifecycle controls
* Develop canonical, conceptual, logical, physical, and semantic data models
* Design enterprise semantic layers, metric definitions, business entities, ontologies, and reusable context models
* Build and integrate knowledge graphs, graph databases, GraphRAG solutions, vector stores, and retrieval architectures
* Establish patterns for metadata management, lineage, data quality, observability, governance, security, privacy, and compliance
* Design data and feature pipelines that support analytics, machine learning, Generative AI, and intelligent agent use cases
* Create reference architectures, technical standards, reusable frameworks, accelerators, and engineering playbooks
* Perform architecture reviews, design validation, code reviews, performance optimization, and technical risk assessments
* Partner with client stakeholders to lead discovery, translate business requirements, and communicate architecture decisions clearly
* Mentor engineers and architects while raising the technical quality and delivery maturity of the team
* Contribute directly to prototypes, pilots, production implementations, and complex troubleshooting when needed
*Required Experience and Skills*
* 10 to 15+ years of experience across data architecture, data engineering, integration, analytics, and enterprise platforms
* Strong combination of strategic data architecture and hands-on engineering expertise
* Demonstrated experience designing and delivering large-scale, production-grade enterprise data solutions
* Deep understanding of the complete data lifecycle, from creation and ingestion through processing, consumption, retention, archival, and deletion
* Strong expertise in data modeling, including conceptual, logical, physical, canonical, and semantic models
* Extensive experience with ETL, ELT, CDC, APIs, event-driven integration, streaming, orchestration, and data activation
* Hands-on experience with modern cloud data platforms such as Snowflake, Databricks, AWS, Azure, or Google Cloud
* Strong knowledge of data warehousing, lakehouse architectures, data lakes, data mesh, data fabric, virtualization, and federated query patterns
* Practical experience with data governance, metadata, lineage, quality, observability, master data, access controls, and regulatory requirements
* Deep understanding of reusable data products, data contracts, domain ownership, SLAs, and federated governance
* Strong knowledge of analytics, BI, self-service data consumption, feature stores, and AI-ready data foundations
* Excellent problem-solving, communication, documentation, and stakeholder-management skills
* Ability to explain complex technical concepts clearly to both executives and engineering teams
AI, Semantic, and Context Engineering Experience
*The ideal candidate will also bring practical experience in several of the following areas:*
* Large language models, Generative AI, intelligent agents, and enterprise AI architectures
* RAG, GraphRAG, knowledge graphs, graph databases, and vector databases
* Ontologies, semantic modeling, enterprise semantic layers, and metric frameworks
* Metadata-driven automation, active metadata, policy enforcement, and context engineering
* AI evaluation, observability, grounding, hallucination reduction, security, and responsible AI controls
* Integration of enterprise data platforms with intelligent applications and agent workflows
* AI-enabled data quality, metadata enrichment, lineage discovery, and engineering automation
*AI-Native Engineering Skills*
We are looking for someone who actively uses modern AI tools to improve engineering productivity and solution quality.
Relevant experience may include:
* Claude Code, Cursor, GitHub Copilot, Windsurf, OpenAI, Gemini, or equivalent AI-assisted development tools
* Agentic development frameworks and AI orchestration platforms
* Model Context Protocol architectures and tool-enabled agent patterns
* AI-assisted software engineering, testing, documentation, data modeling, and code generation
* Autonomous agents, workflow automation, prompt engineering, and structured output patterns
* Using AI to accelerate delivery while maintaining human validation, security, governance, and engineering rigor
*Leadership and Startup Mindset*
* Comfortable operating in an early-stage, high-growth environment
* Able to work independently, move quickly, and deliver with limited supervision
* Willing to move between architecture, engineering, client discussions, and delivery execution
* Strong sense of ownership, accountability, urgency, and attention to quality
* Customer-first mindset with a focus on measurable outcomes
* Comfortable challenging assumptions and proposing better technical approaches
* Passionate about learning, experimentation, innovation, and emerging technologies
* Able to mentor others while remaining hands-on when the situation requires it
* Interested in helping build a company, not only completing assigned project tasks
*Education*
* Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline
* Relevant cloud, data platform, architecture, graph technology, or AI certifications are beneficial
*Why Join Context66*
* Help build a modern Data, AI, and Enterprise Architecture company from the ground up
* Work directly with experienced technology leaders and enterprise clients
* Solve complex, high-value business and architecture problems
* Build modern data platforms, semantic layers, knowledge graphs, GraphRAG systems, and production AI capabilities
* Work with AI-enabled engineering methods and next-generation delivery accelerators
* Influence technical strategy, architecture standards, service offerings, and reusable intellectual assets
* Grow into broader architecture, engineering leadership, and client-facing responsibilities as the company scales
We are looking for builders who combine architecture depth, engineering discipline, curiosity, and a strong commitment to customer outcomes.
Job Type: Full-time
Application Question(s):
* What is your expected Compensation ( Monthly/ USD)
* Have you personally designed and delivered ETL/ELT pipelines, APIs, CDC, streaming integrations, data models, and governed data products?
* Do you have 10 or more years of experience across data architecture, data engineering, integration, and enterprise data platforms?
* Do you have practical experience with at least two of the following: Knowledge Graphs, GraphRAG, ontologies, semantic layers, vector databases, RAG, or enterprise AI architectures?
* Do you have hands-on experience designing and implementing production-grade data solutions using Snowflake, Databricks, AWS, Azure, or Google Cloud?
Work Location: Remote

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