Data Architect

About the Role

We are looking for an experienced Data Architect to design, oversee, and continuously evolve our data infrastructure. In this role, you will be the strategic owner of our data architecture — bridging business requirements with technical solutions across databases, data warehouses, data lakes, and integration systems. You will work closely with engineering, analytics, and leadership teams to build scalable, secure, and high-performing data platforms.

What You’ll Do

Architecture & Design

• Design and oversee the development of the overall data architecture, including databases, data warehouses, data lakes, and data integration systems.
• Translate complex business requirements into robust, forward-looking architecture solutions that support both current and future organisational needs.
• Create and maintain comprehensive documentation including data flow diagrams, data models, and system integration blueprints.

Data Management & Governance

• Define and implement data management processes covering data modelling, metadata management, data quality, and governance frameworks.
• Ensure data security and regulatory compliance by designing and enforcing appropriate access controls and data protection mechanisms.

Optimisation & Innovation

• Optimise data architectures for performance, scalability, and cost-efficiency across both on-premise and cloud environments.
• Stay current with emerging trends and technologies in data architecture, proactively applying relevant innovations to enhance our data infrastructure.

Collaboration & Leadership

• Partner with stakeholders across the business to align data architecture with strategic goals.
• Provide technical guidance and best practices to data engineers, analysts, and developers on architecture design and implementation.

Requirements

Experience

• 7+ years of experience in data architecture, data engineering, or related disciplines.
• 4+ years of hands-on experience with Databricks.

Technical Skills

• Strong understanding of data management principles: data modelling, ETL/ELT processes, data integration, and data warehousing.
• Proven experience with relational and NoSQL databases, data lakes, and big data technologies (e.g., Hadoop, Spark, Kafka).
• Proficiency in data modelling tools and techniques, with solid knowledge of data governance and data quality frameworks.
• Experience with cloud platforms (AWS, GCP, Azure) and modern data architectures, including serverless and microservices patterns.

Education

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

Soft Skills

• Strong analytical and problem-solving skills, with a demonstrated ability to design and implement complex, large-scale data systems.
• Excellent communication and leadership skills, with the ability to influence stakeholders and work effectively across cross-functional teams.