Databricks Data Architect

As a Senior Databricks Data Architect, you’ll play a pivotal role in designing and delivering modern data platforms that transform how organisations leverage data. You’ll work at the intersection of architecture, engineering and business strategy, helping clients move from legacy environments to scalable, cloud-native data ecosystems.

This is an opportunity to influence architecture decisions, establish data engineering best practices and drive the adoption of modern data mesh principles across complex enterprise environments.

What You’ll Be Doing

• Architect and deliver modern data solutions using Databricks, Spark, PySpark and SQL
• Design scalable batch and real-time data pipelines that ingest data from legacy and modern platforms
• Lead the development of cloud-based data lake architectures within AWS
• Build streaming data solutions using Kafka
• Design and implement Medallion Architecture (Bronze, Silver, Gold layers) to support analytics and business intelligence
• Create reusable, domain-driven data products aligned to Data Mesh principles
• Drive data quality, governance, security and operational excellence across the platform
• Collaborate with stakeholders, engineering teams and business domains to enable self-service analytics and data-driven decision making

• Provide technical leadership and architectural direction on large-scale transformation programmes, You’ll join a globally respected technology consulting business recognised for delivering large-scale digital transformation programmes across multiple industries. With significant investment in data, cloud and AI, this is an opportunity to work on high-profile projects, access cutting-edge technologies and collaborate with some of the industry’s most talented specialists. Skills

• Spark
• PySpark

• Strong hands-on expertise with Databricks
• Extensive experience using Spark, PySpark and SQL
• Proven track record designing and implementing data lake architectures
• Experience building both batch and streaming data pipelines
• Strong knowledge of Kafka
• Good understanding of AWS data services, particularly S3
• Knowledge of modern data architectures including Data Mesh and data product ownership models
• Ability to engage with technical and non-technical stakeholders across all levels