Senior Data Architect

Responsibilities

• Data Architecture & Modeling: Define the target data architecture for multi-cloud cost, usage, resource, contract, financial, metadata, and operational datasets.
• Design conceptual, logical, and physical data models optimized for BigQuery analytical workloads
• Documentation & Governance
• Create source-to-target mappings, transformation rules, data contracts, lineage documentation, and business definitions. Define clear ownership boundaries across raw, standardized, curated, and analytics-ready data layers
• Semantic & Domain Modeling: Establish canonical entities, domain models, semantic datasets, and reusable dimensions for traditional reporting as well as modern AI-agent use cases
• Integration & Ingestion
• Design integration patterns for APIs, files, databases, event streams, and semi-structured enterprise data. Ensure data is properly mapped, normalized, and reconciled
• AI & Agent Readiness
• Partner with AI Engineers to design safe, discoverable, read-only BigQuery datasets and MCP tools for agent access. Define query and schema standards that enable reliable agent reasoning, structured responses, analytics, and recommendations
• Performance & Cost Optimization: Review SQL queries, data pipelines, schemas, and integration designs for quality, scalability, maintainability, performance, and cost efficiency. Define BigQuery best practices for partitioning, clustering, materialized views, and query optimization

Languages