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Remote in Brazil, & 2 others
Data Solution Architecture& 15 others
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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