Overview:
The Data Architect defines and governs the end-to-end data and analytics architecture, designing scalable, secure, and future-ready ecosystems across OCI, Snowflake, and BI platforms. The role enables advanced analytics and ML by establishing medallion architecture, semantic layers, and ML Ops-ready data foundations aligned to business strategy.
Responsibilities:
Enterprise Architecture & Roadmap Alignment
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Develop and maintain architecture blueprints aligned with initiatives such as ML Data Warehouse, Semantic Layer, and Medallion Architecture data warehousing.
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Translate roadmap priorities into actionable architecture designs that support model deployment, governance, and advanced analytics.
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Define and enforce data governance frameworks, including lineage, metadata, and compliance standards
Platform Integration & Enablement
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Architect solutions for OCI-based ML Data Warehouse, feature stores, and curated datasets.
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Enable interoperability between ML Ops pipelines, semantic layers, and BI platforms (Tableau Cloud, PowerBI).
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Evaluate emerging technologies for natural language querying and reinforcement learning ecosystems.
Scalability & Performance Optimization
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Design multi-cloud or hybrid architectures for resilience and cost efficiency.
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Optimize infrastructure for high-performance analytics and ML workloads using containerization and orchestration tools.
Future-Ready Capabilities
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Lay the foundation for advanced features such as automated retraining, semantic-driven insights, and natural language data querying.
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Support integration of reinforcement learning and real-time analytics into the architecture.
Requirements:
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5+ years in data or enterprise architecture roles with strong experience in analytics ecosystems.
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Proficiency in OCI, Snowflake, Azure services, and BI platforms (Tableau Cloud, Power BI).
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Familiarity with ML Ops concepts, feature stores, and CI/CD for analytics workloads.
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Strategic & Leadership Skills
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Ability to align architecture decisions with business objectives and roadmap priorities.
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Strong collaboration skills across engineering, data science, and business teams.
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Tools & Technologies
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Understanding of semantic layer architecture and natural language query enablement.
