Senior Data Architect / Data Engineer

Location: Primary: Hyderabad, India. Other locations: Rest of India, Romania, Colombia, and MexicoEmployment Type: Full-time, On-siteAbout Context66Context66 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 OverviewWe 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 ResponsibilitiesDesign end-to-end enterprise data architectures across structured, unstructured, streaming, batch, and event-driven dataDefine current-state, transition-state, and target-state architectures aligned with business outcomesDesign and implement modern data platforms, including data warehouses, data lakes, lakehouses, data mesh, data fabric, and federated data architecturesBuild scalable data ingestion, integration, transformation, orchestration, and activation pipelinesDefine integration patterns across ETL, ELT, APIs, CDC, messaging, streaming, micro-batch, virtualization, and zero-copy architecturesDesign reusable, governed data products with clear ownership, contracts, SLAs, quality expectations, and lifecycle controlsDevelop canonical, conceptual, logical, physical, and semantic data modelsDesign enterprise semantic layers, metric definitions, business entities, ontologies, and reusable context modelsBuild and integrate knowledge graphs, graph databases, GraphRAG solutions, vector stores, and retrieval architecturesEstablish patterns for metadata management, lineage, data quality, observability, governance, security, privacy, and complianceDesign data and feature pipelines that support analytics, machine learning, Generative AI, and intelligent agent use casesCreate reference architectures, technical standards, reusable frameworks, accelerators, and engineering playbooksPerform architecture reviews, design validation, code reviews, performance optimization, and technical risk assessmentsPartner with client stakeholders to lead discovery, translate business requirements, and communicate architecture decisions clearlyMentor engineers and architects while raising the technical quality and delivery maturity of the teamContribute directly to prototypes, pilots, production implementations, and complex troubleshooting when neededRequired Experience and Skills10 to 15+ years of experience across data architecture, data engineering, integration, analytics, and enterprise platformsStrong combination of strategic data architecture and hands-on engineering expertiseDemonstrated experience designing and delivering large-scale, production-grade enterprise data solutionsDeep understanding of the complete data lifecycle, from creation and ingestion through processing, consumption, retention, archival, and deletionStrong expertise in data modeling, including conceptual, logical, physical, canonical, and semantic modelsExtensive experience with ETL, ELT, CDC, APIs, event-driven integration, streaming, orchestration, and data activationHands-on experience with modern cloud data platforms such as Snowflake, Databricks, AWS, Azure, or Google CloudStrong knowledge of data warehousing, lakehouse architectures, data lakes, data mesh, data fabric, virtualization, and federated query patternsPractical experience with data governance, metadata, lineage, quality, observability, master data, access controls, and regulatory requirementsDeep understanding of reusable data products, data contracts, domain ownership, SLAs, and federated governanceStrong knowledge of analytics, BI, self-service data consumption, feature stores, and AI-ready data foundationsExcellent problem-solving, communication, documentation, and stakeholder-management skillsAbility to explain complex technical concepts clearly to both executives and engineering teamsAI, Semantic, and Context Engineering ExperienceThe ideal candidate will also bring practical experience in several of the following areas:Large language models, Generative AI, intelligent agents, and enterprise AI architecturesRAG, GraphRAG, knowledge graphs, graph databases, and vector databasesOntologies, semantic modeling, enterprise semantic layers, and metric frameworksMetadata-driven automation, active metadata, policy enforcement, and context engineeringAI evaluation, observability, grounding, hallucination reduction, security, and responsible AI controlsIntegration of enterprise data platforms with intelligent applications and agent workflowsAI-enabled data quality, metadata enrichment, lineage discovery, and engineering automationAI-Native Engineering SkillsWe 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 toolsAgentic development frameworks and AI orchestration platformsModel Context Protocol architectures and tool-enabled agent patternsAI-assisted software engineering, testing, documentation, data modeling, and code generationAutonomous agents, workflow automation, prompt engineering, and structured output patternsUsing AI to accelerate delivery while maintaining human validation, security, governance, and engineering rigorLeadership and Startup MindsetComfortable operating in an early-stage, high-growth environmentAble to work independently, move quickly, and deliver with limited supervisionWilling to move between architecture, engineering, client discussions, and delivery executionStrong sense of ownership, accountability, urgency, and attention to qualityCustomer-first mindset with a focus on measurable outcomesComfortable challenging assumptions and proposing better technical approachesPassionate about learning, experimentation, innovation, and emerging technologiesAble to mentor others while remaining hands-on when the situation requires itInterested in helping build a company, not only completing assigned project tasksEducationBachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related disciplineRelevant cloud, data platform, architecture, graph technology, or AI certifications are beneficialWhy Join Context66Help build a modern Data, AI, and Enterprise Architecture company from the ground upWork directly with experienced technology leaders and enterprise clientsSolve complex, high-value business and architecture problemsBuild modern data platforms, semantic layers, knowledge graphs, GraphRAG systems, and production AI capabilitiesWork with AI-enabled engineering methods and next-generation delivery acceleratorsInfluence technical strategy, architecture standards, service offerings, and reusable intellectual assetsGrow into broader architecture, engineering leadership, and client-facing responsibilities as the company scalesWe are looking for builders who combine architecture depth, engineering discipline, curiosity, and a strong commitment to customer outcomes.