Databricks Architect

We are looking for an experienced Databricks Architect to design and lead enterprise-scale Lakehouse solutions. The role requires deep expertise across Databricks, Delta Lake, Unity Catalogue, Apache Spark/PySpark, cloud platforms, and streaming technologies, along with a strong track record in enterprise architecture and technical leadership.

Key Responsibilities

• Define and own enterprise Lakehouse architecture, including platform design, governance, security and data access patterns.
• Architect scalable, reliable and high-performance Databricks platforms and guide platform modernisation, migration and integration.
• Lead cloud data transformation initiatives across AWS, Azure and/or GCP, working closely with engineering, data and business stakeholders.
• Establish architecture standards for Delta Lake, Unity Catalogue, Apache Spark and PySpark, including data governance, lineage, quality and security controls.
• Design batch and real-time data solutions using Kafka and streaming technologies. • Drive DataOps and CI/CD practices for data platforms, including automated deployment, testing, monitoring and release governance.
• Ensure platform performance, scalability, reliability and cost-effectiveness through architecture reviews, optimisation, and engineering standards.
• Provide technical leadership, architecture guidance and mentoring to engineering teams while collaborating with enterprise and cloud stakeholders.
• Create and maintain architecture documentation, design decisions, standards and implementation roadmaps.

Required Expertise

• Strong hands-on architecture experience with Databricks, Delta Lake and Unity Catalog.
• Deep knowledge of Apache Spark and PySpark for large-scale data processing.
• Strong cloud architecture experience with one or more of AWS, Azure or GCP.
• Experience designing Kafka-based and other real-time / streaming data architectures.
• Strong understanding of enterprise data architecture, Lakehouse patterns, security, governance, integration and platform scalability.
• Practical experience with DataOps, CI/CD and modern engineering practices for data platforms.

Good to Have

• The successful candidate should demonstrate strong architecture-level capability across the following technology areas.
• Databricks Delta Lake Unity Catalog Apache Spark PySpark AWS Azure GCP Kafka Streaming DataOps CI/CD Lakehouse Architecture Cloud Platforms Data Governance Platform Security Required Qualifications
• Bachelor's degree in Computer Science, Engineering or a related discipline.
• Approximately 12-15 years of overall experience, with a proven track record in enterprise data/platform architecture.
• Demonstrated experience designing and delivering enterprise-scale Databricks and cloud data solutions.
• Databricks and/or relevant cloud certifications are preferred.
• Strong stakeholder communication and technical leadership skills, with the ability to translate business requirements into scalable architecture.

What We Are Looking For

• An architect who can operate at both strategic and technical levels.
• Someone comfortable owning architecture decisions from design through implementation.
• A strong collaborator who can work across cloud, data engineering, platform, security and business teams.
• Candidates who can join quickly are preferred.