Data Architect
Role details
Job location
Tech stack
Job description
We are seeking a Senior Databricks Architect to lead the design and delivery of scalable, high-performance data platforms built on Databricks. This is a strategic role requiring strong architectural experience, hands-on design capability, and a deep understanding of modern data ecosystems., * Design end-to-end data architectures using Databricks for analytics, data engineering, and data science use cases.
- Lead and support data platform migrations into Databricks from legacy or alternative data platforms.
- Define architectural standards, best practices, and reference patterns for Databricks implementations.
- Collaborate with data engineers, platform teams, and stakeholders to translate business requirements into scalable technical solutions.
- Ensure solutions meet performance, security, scalability, and cost-optimization requirements.
- Provide technical leadership and architectural governance across Databricks initiatives.
- Review existing data architectures and recommend improvements or modernisation strategies.
- Support teams with architectural guidance, troubleshooting, and design reviews.
Requirements
The ideal candidate will have several years' experience operating at architect level, with proven success designing and/or migrating data platforms into Databricks. Candidates with strong architecture backgrounds on comparable platforms (such as Snowflake) will also be considered, provided they hold relevant Databricks certifications., * Essential Skills & ExperienceProven experience working as a Data Architect / Platform Architect at a senior level.
- Hands-on experience designing solutions within the Databricks ecosystem OR strong architectural experience on a competing platform (e.g. Snowflake) combined with Databricks certifications.
- Demonstrated experience with data platform migrations, modernisation, or large-scale data transformations.
- Strong understanding of data architecture principles, including:
- Data lakes / lake house architectures.
- Data modelling and data integration patterns
- Performance optimisation and scalability
- Experience working with cloud-based data platforms.
- Strong stakeholder communication and documentation skills., * Databricks certifications (Data Engineer, Data Architect, or equivalent).
- Experience designing solutions prior to Databricks (traditional data warehouses, big data platforms, or cloud-native data stacks).
- Knowledge of modern data engineering tools and frameworks.
- Experience operating in complex enterprise environments