Data Architect

Softlanding; Portugal; Remote; EUR 70,000 - 90,000; Full time

Job summary

Softlanding in Portugal seeks an experienced Data Architect to lead the design and implementation of a modern enterprise data platform built on Azure Databricks. You will define target-state data architecture, establish modeling standards, and design scalable data integration and governance frameworks aligned with business objectives.

The role combines strategic architecture leadership with hands-on solution design, reviews, and guidance across Data Engineers, Analytics teams, and Enterprise

Qualifications

• 7+ years of experience in Data Architecture.
• 3+ years hands-on Azure Databricks architecture experience.
• Strong enterprise data modeling skills (conceptual, logical, physical).
• Proven experience designing Data Warehouses, Data Lakes, or Lakehouse platforms.
• Strong understanding of Lakehouse architecture and modern data platform design.
• Strong SQL skills and analytical data modeling knowledge.
• Experience using Azure cloud services for data platforms.
• Knowledge of data governance, metadata management, lineage, and security.
• Excellent communication with business stakeholders and cross-functional teams.
• Must have: Valid Visual Studio Professional license.

Responsibilities

• Define target-state data architecture for the enterprise data platform.
• Design scalable Lakehouse architectures using Azure Databricks.
• Develop conceptual, logical, and physical data models aligned with business needs.
• Establish enterprise standards for data modeling, integration, storage, and governance.
• Define patterns for ingestion, transformation, consumption, and integration across systems.
• Ensure designs meet scalability, performance, security, and cost targets.
• Guide platform evolution and contribute to the architecture roadmap.
• Lead data modeling activities and promote reuse across domains.
• Review models and align with enterprise data products.

Skills

Data Architecture

Azure Databricks

Data Modeling

Data Warehouses/Lakes

SQL Proficiency

Azure Cloud

Data Governance

Stakeholder Communication

Team Collaboration

Tools

Databricks Unity Catalog

Job description

We are seeking an experienced Data Architect to lead the design and implementation of a modern enterprise data platform built on Azure Databricks. The successful candidate will define the target-state data architecture, establish enterprise data modeling standards, and design scalable data integration and governance frameworks aligned with business objectives.

The role combines strategic architecture leadership with hands‑on involvement in solution design, technical reviews, and implementation guidance. The Data Architect will work closely with business stakeholders, Data Engineers, Analytics teams, and Enterprise Architects to deliver a secure, scalable, high‑performance Lakehouse platform that supports enterprise reporting, analytics, and future business needs.

Key Responsibilities

1. Data Architecture and Solution Design

• Define and maintain the target-state data architecture for the enterprise data platform.
• Design scalable Lakehouse architectures using Azure Databricks and industry best practices.
• Develop conceptual, logical, and physical data models aligned with business and technical requirements.
• Establish enterprise standards for data modeling, data integration, data storage, and data governance.
• Define architecture patterns for data ingestion, transformation, consumption, and integration across enterprise systems.
• Ensure architecture designs meet requirements for scalability, performance, security, reliability, and cost efficiency.
• Guide platform evolution and contribute to the enterprise data architecture roadmap.

2. Enterprise Data Modeling

• Lead enterprise-wide data modeling activities and define reusable modeling standards.
• Translate business requirements into scalable and maintainable data models.
• Define enterprise data structures, business entities, relationships, and common business definitions.
• Design data models for Data Warehouses, Data Lakes, Lakehouse platforms, and analytical consumption layers.
• Review and approve solution‑specific data models developed by Data Engineers and delivery teams.
• Promote consistency and reuse of data models across business domains and data products.
• Ensure data models support reporting, analytics, data integration, and future business requirements.

3. Data Governance, Security, and Compliance

• Define and implement enterprise data governance principles, standards, and architecture guidelines.
• Establish practices for data lineage, metadata management, data cataloging, and data ownership.
• Define data access patterns, security models, and role‑based access control.
• Ensure alignment with enterprise security policies, regulatory requirements, and data protection standards.
• Support the implementation of data governance capabilities within the Databricks Lakehouse environment.
• Promote data quality, consistency, traceability, and trusted data consumption across the platform.

4. Databricks and Azure Data Platform Architecture

• Design and guide the implementation of enterprise data solutions using Azure Databricks.
• Define architectural patterns for Lakehouse storage, data processing, integration, and analytical consumption.
• Establish best practices for data organization, workload management, performance optimization, and platform scalability.
• Guide Data Engineers in implementing architecture standards and reusable technical components.
• Evaluate platform capabilities and recommend appropriate technologies and design patterns.
• Support technical decision‑making related to Azure cloud services and enterprise data platform components.

5. Delivery Support and Technical Leadership

• Work closely with Data Engineers to translate architecture designs into production‑ready solutions.
• Review technical designs, data models, integration patterns, and architecture decisions.
• Provide guidance on performance optimization, scalability, maintainability, and cost management.
• Identify architectural risks, dependencies, and opportunities for platform improvement.
• Ensure implementation aligns with target architecture and established engineering standards.
• Support delivery planning and contribute to the continuous improvement of the data platform.

6. Stakeholder Management and Collaboration

• Conduct business and technical workshops to gather requirements and define architecture solutions.
• Collaborate with business stakeholders, Enterprise Architects, Data Engineers, BI teams, and Analytics teams.
• Translate complex technical concepts into clear recommendations for technical and non‑technical audiences.
• Communicate architecture decisions, trade‑offs, risks, and recommendations effectively.
• Act as a trusted advisor on enterprise data architecture, data modeling, and platform strategy.
• Ensure architecture decisions align with business priorities and long‑term enterprise data objectives.

Mandatory Skills and Experience

• Minimum 7+ years of experience in Data Architecture.
• Minimum 3+ years of hands‑on Azure Databricks architecture experience.
• Strong background in enterprise data modeling, including conceptual, logical, and physical data models.
• Proven experience designing enterprise Data Warehouses, Data Lakes, or Lakehouse platforms.
• Strong understanding of Lakehouse architecture and modern enterprise data platform design principles.
• Strong SQL skills and understanding of data structures, relationships, and analytical data models.
• Experience designing and implementing data architectures using Azure cloud services.
• Expertise in data integration patterns, enterprise data modeling standards, and data architecture principles.
• Understanding of data governance, metadata management, lineage, cataloging, and data security.
• Strong experience communicating with business stakeholders and translating business requirements into architecture solutions.
• Proven ability to collaborate with Data Engineers, Enterprise Architects, and Analytics teams.
• Excellent communication, presentation, stakeholder management, and workshop facilitation skills.
• Mandatory: Valid Visual Studio Professional license and the ability to work within the organization's licensed development environment.

Preferred Skills

• Experience designing and implementing Enterprise Data Hubs or enterprise-wide data platforms.
• Experience in the consumer goods, FMCG, or retail industries.
• Understanding of enterprise data domains, business entities, and cross-domain data integration.
• Experience defining enterprise data architecture standards and target-state roadmaps.
• Familiarity with Databricks governance and cataloging capabilities, including Unity Catalog.
• Experience supporting enterprise data modernization and cloud migration initiatives.
• Knowledge of data platform performance optimization, scalability, and cost management.

Key Competencies

• Strategic thinking and enterprise architecture leadership.
• Strong analytical and problem‑solving capabilities.
• Ability to translate business needs into scalable technical architecture.
• Excellent stakeholder engagement and workshop facilitation.
• Strong decision‑making skills and the ability to evaluate architecture trade‑offs.
• Ability to influence technical teams and drive adherence to architecture standards.
• Effective collaboration across business, architecture, engineering, and analytics functions.