Data Architect

Job Summary

The Data Architect position is responsible for designing and implementing the architecture of data systems to ensure data is stored, processed, and accessed in an efficient, secure, and scalable manner. This role plays a key part in defining data strategies, developing and maintaining data models, and enabling seamless data integration across platforms. Working closely with business and technology stakeholders, the Data Architect ensures data architecture aligns with business needs, governance standards, and future growth, while continuously evolving the data ecosystem through best practices and emerging technologies.

Main Duties & Responsibilities

• Data Architecture Design: Design, implement, and maintain scalable, reliable, and efficient data architectures aligned with business strategy and data management objectives.

• Data Modeling: Develop and govern conceptual, logical, and physical data models to support business requirements, analytics, and data governance standards.

• Data Integration: Architect and oversee data integration solutions to ensure seamless and reliable data flow across data lakes, data warehouses, operational systems, and external sources.

• Scalability, Performance & Availability: Optimize data platforms for performance, scalability, resilience, and high availability to support large data volumes and business growth.

• Cloud & Platform Architecture: Design and implement cloud-based data solutions using platforms such as AWS, Azure, or Google Cloud, ensuring flexibility, cost efficiency, and scalability.

• Big Data & Advanced Analytics Enablement: Architect solutions for big data processing and analytics, enabling efficient storage, processing, and analysis of large and complex datasets.

• Data Governance & Quality: Define and enforce data governance, data quality, and metadata standards across the data architecture, ensuring consistency, reliability, and compliance.

• Data Security & Privacy: Ensure data architectures comply with security and privacy regulations (e.g. GDPR, CCPA), including access controls, encryption, data masking, and secure design principles.

• Stakeholder Collaboration: Partner with business leaders, data analysts, data scientists, engineers, and IT teams to translate business needs into robust, future-ready technical solutions.

• Architecture Documentation & Standards: Produce and maintain clear architecture documentation, design principles, standards, and best practices to support reuse and knowledge sharing.

• Continuous Improvement & Innovation: Stay current with emerging data technologies and industry trends, continuously evolving the data architecture to meet changing business and technological needs.

Core Competencies and Requirements

Education

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field

• Master’s degree in Data Science, Computer Science, or Information Management is an advantage

• Relevant certifications (e.g. cloud platform certifications, data architecture, or data management) are a plus

Work Experience

• 5+ years of professional experience in data architecture, data engineering, or a related field, with a strong understanding of data modeling concepts, data architecture and design principles, and modern data management technologies.

• Proven experience designing and implementing data systems, including relational databases, data warehouses, data lakes, and cloud-based data architectures, with a focus on scalability, performance, and reliability.

Technical Skills

• Strong expertise in enterprise application platforms, including ERP, HRIS, Finance, Procurement, and other corporate support systems, within complex organizational environments.

• Solid understanding of platform lifecycle management, including system upgrades, patching, maintenance, and end-of-life planning.

• Proven experience with integration platforms and middleware, supporting data and process integration across on-premise, cloud, and hybrid IT landscapes.

• Strong knowledge of IT service management, security principles, identity and access management, and audit and compliance requirements.

• Ability to define, monitor, and optimize platform KPIs related to system reliability, performance, cost efficiency, and user experience.

Language Skills

• Fluent in English (written and spoken); additional regional languages are an asset.

Required Competencies

Strategic & Systems Thinking: Thinks holistically across complex environments, understanding interdependencies and balancing standardization, simplicity, and scalability.

Analytical Problem Solving: Analyzes complex situations, identifies root causes, and develops sound solutions in ambiguous contexts.

Decision Making & Ownership: Makes well-reasoned decisions within scope and takes ownership for quality and outcomes.

Business Understanding & Context Awareness: Understands business priorities and constraints and applies this context to practical, value-driven decisions.

Collaboration & Influence: Collaborates effectively with stakeholders, communicating clearly and influencing through expertise and constructive challenge.

Quality, Governance & Risk Awareness: Applies standards and controls with attention to quality, governance, and risk.