We are a global technology consultancy with a trademarked, AI-first approach—Gen-e2. It redefines how enterprises build digital products and transform their organizations with AI. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company.
We are small enough to care locally, big enough to deliver globally (10 countries, 450+ experts from 50+ nationalities)
We are becoming an agentic organization, adopting the AI-native operating model we bring to our clients.
We are robust and resilient (100% independent, 0 debt, founded 2009)
We are AI-native professionals who invest in what we believe and work as a collective intelligence
We are positive, courageous and deliver at the leading edge.
As a Data Architect, you will take a leading role in designing, evolving, and optimizing data architecture for innovative, scalable, and secure solutions. You will collaborate closely with data engineers, analytics teams, business stakeholders, and IT leadership to deliver data strategies that power decision-making and digital transformation.
Key Responsibilities
Strategy & Architecture
Define, evolve, and document the organization’s data architecture aligned with business and IT strategy.
Design enterprise data models (conceptual, logical, and physical), establishing naming conventions and modeling standards.
Assess and recommend data technologies (Data Lake, Lakehouse, Mesh, Warehouse) based on evolving business needs.
Governance, Privacy & Quality
Define policies and standards for data governance, quality, privacy, cataloging, and lineage.
Lead adoption of metadata management and data discovery tools across teams.
Ensure compliance with internal and external data regulations and security requirements.
Data Integration & Design
Architect data integration solutions (ETL/ELT, real-time and batch pipelines).
Ensure interoperability across domains, sources, and consumers using principles such as Data Mesh.
Define integration patterns and data federation frameworks to deliver a 360° data view.
Collaboration & Leadership
Act as a technical reference in data architecture, guiding engineering, analytics, and business teams.
Promote adoption of data models, standards, and best practices across the organization.
Translate business needs into scalable data solutions and facilitate technical-business alignment.
Education
Bachelor’s degree in Mechatronics Engineering, Applied Mathematics, Software Engineering, Computer Science, or related fields.
Preferred certifications: Microsoft Certified, Azure Data Engineer Associate, or relevant cloud and data architecture certifications.
Required Experience
10+ years of experience in Data engineer
3+ years designing cloud-based data architectures (Azure, AWS, or GCP).
2+ years in data architecture, enterprise data modeling, or data governance.
Led data model design (relational, multidimensional, non-relational) for Data Warehouse, Data Lake, or Lakehouse architectures.
Participated in multi-source data integration projects (on-premise, cloud, external sources).
In-depth knowledge of data governance frameworks including quality, cataloging, privacy, and compliance.
Experience with modern architectures (Data Mesh, Lakehouse) and cataloging tools (Purview, Unity Catalog) is a plus.
Technical Expertise
Data Modeling: Conceptual, logical, physical modeling; normalization; relational and non-relational design.
Architectures: Data Warehouse, Data Lake, Lakehouse, Data Mesh.
Governance: Data lineage, quality, privacy, RBAC, metadata management.
Platforms: Azure Synapse, Azure Data Lake Gen2, Purview, Unity Catalog, Cosmos DB.
Data Integration: Azure Data Factory, API Management, integration patterns, Azure Databricks.
Infrastructure as Code (IaC): Terraform, Azure DevOps (preferred).
Languages & Tools: SQL, Python (architectural level), JSON, Java, Scala.
CI/CD: Git, Sonar, DevOps best practices.
Leadership & Soft Skills
Systemic Thinking: Designs modular, scalable, and integrated architectures.
Cross-functional Communication: Translates technical and business requirements clearly and effectively.
Reuse Mindset: Focuses on creating shareable and scalable components.
Technical Leadership: Influences technical direction and decision-making across teams.
Complexity Management: Solves high-impact, large-scale technical challenges.
Product & Platform Mindset: Designs with the data consumer experience in mind.
Curiosity & Continuous Learning: Stays ahead of tech trends and promotes innovation.
Use Generative AI coding tools (e.g., GitHub Copilot, Cursor) as a first-class engineering assistant for:
Code scaffolding and refactoring
Code generation and optimisation
Test-cases and documentation generation
Build applications through AI-driven development practices, including:
AI-assisted debugging and troubleshooting
Intelligent code completion and pattern recognition
Automated documentation generation
Apply prompt engineering best practices for reliable, repeatable engineering outcomes.
Validate GenAI output (determinism checks, guardrails, fallback logic).
What We Offer
Stimulating working environments
Unique career path
International mobility
Internal R&D projects (including Gen-e2)
Knowledge sharing
Personalized training via PALO IT Academy
Entrepreneurship & intrapreneurship
For more on our team culture and benefits, check out our careers page.
