Data Architect

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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