Data Architect

Role Overview: You have a strategic role as a Data Architect at XenonStack where you will be responsible for designing, governing, and optimizing enterprise data ecosystems to fuel various systems like LLM training, RAG pipelines, Vision AI, and multi-agent systems. Your role will involve blending data engineering, governance, and architecture leadership to ensure trusted, scalable, and intelligent data infrastructure for XenonStack and its customers. Key Responsibilities: - 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. - Establish standards for data modeling, lineage, quality, and master data management. - Implement governance frameworks to meet enterprise and regulatory needs (GDPR, SOC2, HIPAA). - Architect data pipelines feeding into LLMs, RAG systems, and Vision AI workflows. - Collaborate with AI/ML teams to design high-quality, labeled, and observable datasets. - 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. - Mentor data engineers and platform engineers on best practices. - Partner with Product, AgentOps, and Security teams for reliable, compliant, and cost-optimized data systems. Qualifications Required: Must-Have: - 8-12 years of experience in data engineering, architecture, or analytics platform leadership. - Proven expertise in data modeling, ETL/ELT pipelines, and distributed data systems. - Hands-on experience with big data and analytics frameworks like Spark, Kafka, Delta Lake, Databricks. - Strong knowledge of cloud-native data ecosystems such as AWS Redshift/Glue, Azure Synapse/Data Factory, GCP BigQuery/Dataflow. - Proficiency in SQL, Python, and data orchestration frameworks like 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. Additional Company Details: At XenonStack, the culture is built on bold, human-centric leadership principles fostering a culture of cultivation. Values like Agency, Taste, Ownership, Mastery, Impatience, and Customer Obsession drive the autonomy to innovate and accountability to deliver. The company is committed to accelerating the world's transition to AI + Human Intelligence by architecting trusted data platforms that power enterprise AI adoption.,