{"id":3264738,"url":"https://alion.io/job/kalpavruksh-senior-data-architectlead-data-engineer","title":"Senior Data Architect/Lead Data Engineer","company":{"id":4455719,"name":"Kalpavruksh","domain":"kalpavruksh.com","url":"https://alion.io/company/kalpavruksh","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":29000,"max_usd":62000,"period":"year","method":"role_seniority_country_cell","sample_n":21},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Claude Code","optional":false},{"name":"Context Engineering","optional":false},{"name":"Copilot","optional":false},{"name":"Cursor","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"GraphRAG","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"Windsurf","optional":false}],"status":"live","first_seen_at":"2026-10-26T07:50:04Z","employer_posted_date":null,"last_verified_at":"2026-10-26T07:50:04Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Role Overview : \n\nWe 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.\n\nKey Responsibilities : \n\n- Design end-to-end enterprise data architectures.\n\n- Define current, transition, and target-state architectures.\n\n- Design modern data platforms (warehouses, lakes, lakehouses, mesh, fabric).\n\n- Build scalable ingestion, integration, transformation, orchestration, and activation pipelines.\n\n- Define ETL/ELT/API/CDC/streaming integration patterns.\n\n- Design governed data products.\n\n- Develop conceptual, logical, physical, canonical, and semantic data models.\n\n- Build semantic layers, ontologies, knowledge graphs, GraphRAG, and vector stores.\n\n- Establish metadata, lineage, governance, observability, security, and compliance.\n\n- Support analytics, ML, GenAI, and intelligent agents.\n\n- Create reference architectures and engineering standards.\n\n- Perform architecture reviews and optimization.\n\n- Partner with clients and mentor engineers.\n\nRequired Experience and Skills : \n\n- 10 - 15+ years in data architecture/engineering.\n\n- Strong architecture plus hands-on engineering.\n\n- Enterprise-scale solution delivery.\n\n- Deep data lifecycle expertise and strong data modeling.\n\n- Experience with ETL, ELT, CDC, APIs, streaming.\n\n- Cloud platforms : Snowflake, Databricks, AWS, Azure, GCP.\n\n- Data warehouses, lakehouses, mesh, fabric.\n\n- Governance, metadata, lineage, quality.\n\n- Data products and contracts.\n\n- Analytics and AI-ready foundations.\n\nAI, Semantic, and Context Engineering Experience : \n\n- LLMs, GenAI, intelligent agents.\n\n- RAG, GraphRAG, knowledge graphs, vector databases.\n\n- Ontologies and semantic modeling.\n\n- Metadata-driven automation.\n\n- AI evaluation and responsible AI.\n\nAI-Native Engineering Skills : \n\n- Claude Code, Cursor, GitHub Copilot, Windsurf, OpenAI, Gemini.\n\n- Agentic frameworks, Model Context Protocol, and prompt engineering.\n\nLeadership and Startup Mindset : \n\n- Startup mindset with independent execution.\n\n- Hands-on across architecture and delivery.\n\n- Ownership, accountability, and customer-first approach.\n\nEducation : \n\n- Bachelor's or Master's in a relevant field.\n\n- Relevant cloud/data/AI certifications are a plus.\n\nWhy Join Context66 : \n\n- Build a modern Data, AI, and Enterprise Architecture company.\n\n- Work with experienced leaders and solve high-value problems.\n\n- Influence technical strategy and grow into leadership.\n\n- Opportunity to lead enterprise-scale data transformation initiatives.\n\n- High-impact, client-facing role with strong ownership.\n\nSkills\nData Engineering, Data Modeling, Data Governance, AWS, Azure, Databricks, ETL, Data Architect, Data Warehousing, Snowflake 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