Data Architect

Job Description ABOUT XENONSTACK XenonStack is the fastest-growing  Data and AI Foundry for Agentic Systems , enabling enterprises to gain  real-time and intelligent business insights . We deliver innovation through: Agentic Systems for AI Agents   →  akira.ai Vision AI Platform   →  xenonstack.ai Inference AI Infrastructure for Agentic Systems   →  nexastack.ai Our mission is to accelerate the world’s transition to  AI + Human Intelligence   by designing  scalable, reliable, and AI-ready data platforms   that power next-gen enterprise systems. THE OPPORTUNITY We are seeking a  Data Architect   to design, govern, and optimize  enterprise data ecosystems   that fuel  LLM training, RAG pipelines, Vision AI, and multi-agent systems . This is a strategic role that blends  data engineering, governance, and architecture leadership   — ensuring that XenonStack and its customers operate on  trusted, scalable, and intelligent data infrastructure . KEY RESPONSIBILITIES Data Architecture & Strategy Define and implement  data platform blueprints   across cloud and hybrid environments. Design architectures for  data lakes, warehouses, and real-time streaming pipelines . Ensure alignment with  business goals, AI readiness, and compliance requirements . Enterprise Data Modeling & Governance Establish standards for  data modeling, lineage, quality, and master data management . Implement  governance frameworks   to meet enterprise and regulatory needs (GDPR, SOC2, HIPAA). AI & Analytics Enablement Architect  data pipelines   that feed into  LLMs, RAG systems, and Vision AI workflows . Collaborate with AI/ML teams to design  high-quality, labeled, and observable datasets . Technology & Integration Define reference architectures for  ETL/ELT, vector databases, and knowledge graph integration . Evaluate and select technologies across  AWS, Azure, GCP, and open-source data ecosystems . Leadership & Collaboration Mentor  data engineers and platform engineers   on best practices. Partner with  Product, AgentOps, and Security teams   to ensure reliable, compliant, and cost-optimized data systems. SKILLS & QUALIFICATIONS Must-Have 8–12 years in  data engineering, architecture, or analytics platform leadership . Proven expertise in  data modeling, ETL/ELT pipelines, and distributed data systems . Hands-on with  big data and analytics frameworks   (Spark, Kafka, Delta Lake, Databricks). Strong knowledge of  cloud-native data ecosystems (AWS Redshift/Glue, Azure Synapse/Data Factory, GCP BigQuery/Dataflow) . Proficiency in  SQL, Python, and data orchestration frameworks (Airflow, dbt) . Deep understanding of  data governance, compliance, and security best practices . Good-to-Have Experience with  vector databases (Pinecone, Weaviate, FAISS) and knowledge graphs . Familiarity with  LLM/AI data pipelines and agentic system data needs . Certifications in AWS/Azure/GCP data engineering or architecture. Industry exposure to  BFSI, GRC, SOC, or regulated enterprise environments . WHY SHOULD YOU JOIN US? Agentic AI Product Company Architect data systems that power  enterprise-grade AI agents . A Fast-Growing Category Leader Join one of the fastest-growing  AI Foundries , trusted by Fortune 500 enterprises. Career Mobility & Growth Progress into roles such as  Principal Data Architect, Head of Data Platforms, or AI Systems Architect . Global Exposure Work with enterprises worldwide on  mission-critical data systems . Create Real Impact Your designs will directly influence  AI adoption, enterprise intelligence, and business outcomes . Culture of Excellence Our values —  Agency, Taste, Ownership, Mastery, Impatience, and Customer Obsession   — give you autonomy to innovate and accountability to deliver. Responsible AI First Ensure data platforms are  not just powerful, but trustworthy, explainable, and compliant . XENONSTACK CULTURE – JOIN US & MAKE AN IMPACT At XenonStack, we believe in  shaping the future of intelligent systems . We foster a  culture of cultivation   built on bold, human-centric leadership principles, where  deep work, simplicity, and adoption   define everything we do. Our Cultural Values Agency   – Be self-directed and proactive. Taste   – Sweat the details and build with precision. Ownership   – Take responsibility for outcomes. Mastery   – Commit to continuous learning and growth. Impatience   – Move fast and embrace progress. Customer Obsession   – Always put the customer first. Our Product Philosophy Obsessed with Adoption   – Making AI-ready data architectures accessible and enterprise-grade. Obsessed with Simplicity   – Turning complex data challenges into seamless, intuitive systems. Be a part of our mission to  accelerate the world’s transition to AI + Human Intelligence   — by  architecting the trusted data platforms that power enterprise AI adoption . Requirements Must-Have 8–12 years in data engineering, architecture, or analytics platform leadership. Proven expertise in data modeling, ETL/ELT pipelines, and distributed data systems. Hands-on with big data and analytics frameworks (Spark, Kafka, Delta Lake, Databricks). Strong knowledge of cloud-native data ecosystems (AWS Redshift/Glue, Azure Synapse/Data Factory, GCP BigQuery/Dataflow). Proficiency in SQL, Python, and data orchestration frameworks (Airflow, dbt). Deep understanding of data governance, compliance, and security best practices.