Data Architect

We are seeking a hands-on Data Architect to design and evolve the data foundation for a production AI agent platform focused on cost optimization, anomaly detection, and automated insights. You will define architecture, models, and governed datasets that enable reliable analytics and safe agent access.

Responsibilities

• Define target data architecture across cost, usage, inventory, contract, finance, metadata, and operational domains
• Design conceptual, logical, and physical data models for analytical workloads
• Create source-to-target mappings, transformation rules, data contracts, lineage, and business definitions
• Establish raw, standardized, curated, and analytics-ready data layers with clear ownership boundaries
• Build canonical entities, domain models, semantic datasets, and reusable dimensions for reporting and agent use cases
• Design integration patterns for APIs, files, databases, event streams, and semi-structured sources
• Partner with data engineering to define ingestion, transformation, enrichment, reconciliation, and data quality patterns
• Collaborate with AI engineering to define safe, discoverable, read-only datasets and agent access patterns
• Define query and schema standards that support reliable reasoning, analytics, and recommendations
• Review schemas, SQL, pipelines, and integration designs for scalability, maintainability, performance, and cost efficiency
• Define warehouse optimization standards such as partitioning, clustering, and materialized views
• Establish governance standards for lineage, access control, retention, classification, quality, and freshness
• Provide technical leadership through architecture and code reviews across the data domain

Requirements

• 2+ years data architecture or data engineering experience on analytics platforms
• Stakeholder leadership experience guiding engineers and client stakeholders
• Strong project ownership skills for driving architecture decisions from discovery to delivery
• Advanced SQL skills with hands-on cloud data warehouse experience
• Strong data modeling skills across conceptual, logical, physical, and dimensional models
• Strong Google Cloud Platform skills including BigQuery and core integration services
• Hands-on Python skills for data services, POCs, or API-based integrations
• Strong integration skills with REST APIs, batch processing, and semi-structured data
• Strong data governance knowledge including lineage, access control, and retention
• Strong data quality skills including reconciliation and schema evolution practices
• Strong communication skills for translating business needs into data contracts and standards
• Upper-Intermediate English (B2) proficiency

Nice to have

• Google Cloud BigQuery expertise in performance tuning and cost optimization
• Python proficiency for building data utilities and integration prototypes
• Data governance experience with catalogs, metadata management, and lineage tooling
• Data model experience with semantic layers and domain-driven modeling
• Stakeholder management experience in cross-functional architecture alignment