Data Architect
Role Overview
We are modernizing the Solvace SaaS platform and its data foundations. To support this transformation, we are hiring a Data Architect to define, evolve, and govern the data architecture that underpins Revamp and all data-driven capabilities across the platform.
This is a senior, hands-on, and leadership-oriented Data Architect role.
You will be responsible for actively shaping and validating data architectures, defining core data models, and establishing standards, while contributing directly through design, spikes, and proof-of-concepts. Your work will enable scalable analytics, operational reporting, automation, and AI-enabled capabilities across Solvace, rather than ownership of day-to-day data pipeline execution.
You will work closely with application architects, data engineers, QA, DevOps, DBAs, product, and security stakeholders to ensure that data platforms are reliable, secure, well-governed, and fit for long-term evolution.
This is not a theoretical or ivory-tower role. We are looking for architects who think deeply about data systems, quality, governance and can translate that thinking into clear, actionable foundations that teams can effectively build on, under real-world constraints.
Location: Portugal (Remote)
Contract Type: Contractor
Key Responsibilities
* Own and evolve the enterprise data architecture, spanning operational databases, analytical platforms, and integration layers, with a strong focus on foundations, models and standards
* Define and maintain data models (relational, dimensional) aligned with product and business needs, in close collaboration with application architects.
* Design and guide data platforms including Data Lakes, Lakehouses, and Data Warehouses, ensuring consistency with core operational data models
* Define standards for data integration via APIs, ETL/ELT pipelines, and event-based data flows
* Ensure data quality, lineage, cataloging, and governance are designed into solutions from day one
* Partner with security and compliance stakeholders to ensure alignment with information security and regulatory requirements (e.g., LGPD)
* Stay hands-on by leading architectural design activities, technical spikes, proof-of-concepts, and architecture validations
* Collaborate closely with Application Architects, QA, Data Engineering, DBA and DevOps teams to ensure data solutions are testable, observable, and production-ready
* Support AI, ML, and GenAI use cases by ensuring appropriate data availability, structure, and governance, rather than direct model development
* Guide standards for versioning, CI/CD, and automation practices for data pipelines and schemas, in collaboration with Data Engineering teams
* Act as a technical reference and mentor for engineering and data teams
* Drive a root-cause mindset: address systemic data issues at the architectural level, not just downstream symptoms
Requirements
Essential
* 7+ years of experience working with data-intensive systems, including ownership of data architecture decisions
* Strong experience designing relational, dimensional, and event-driven data models
* Hands-on experience with relational databases (e.g., PostgreSQL, SQL Server) and with NoSQL technologies
* Experience designing and operating Data Lakes, Lakehouses, and/or Data Warehouses, in alignment with operational data models
* Experience with data integration patterns, including APIs, ETL/ELT pipelines, and event-based data flows, at an architectural level
* Familiarity with cloud platforms (AWS, Azure, or GCP) and hybrid data environments
* Architectural understanding of event-driven or streaming platforms, including CDC-based approaches (e.g., Kafka-style architectures, database CDC patterns); hands-on implementation experience is a plus
* Strong understanding of data governance, quality, lineage, and cataloging concepts
* Experience collaborating with DevOps teams on CI/CD, automation standards, and operational readiness
* Proven ability to operate as a hands-on architect, combining architectural ownership with practical validation and technical guidance
* Fluent English. Portuguese is a plus
Desirable
* Experience supporting SaaS platforms with complex, evolving data domains
* Experience enabling AI, ML, or GenAI initiatives through data architecture and data readiness
* Experience communicating data architectures using clear diagrams and documentation
* Prior experience in platform modernization or large-scale data transformation initiatives
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