Platform Engineer

• Design, build and enhance a secure, scalable and reliable Databricks platform
• Develop and maintain batch and real-time data pipelines using Databricks, Apache Spark and Delta Lake
• Contribute to platform architecture, engineering standards and best practices across the data estate
• Work with Product, Analytics and Data Science teams to deliver effective data platform solutions
• Support platform operations, monitoring, performance optimisation and reliability
• Apply Infrastructure as Code principles to support consistent and efficient platform management
• Share technical knowledge and contribute to continuous improvement across the engineering team, * 25 days Annual leave allowance, bank holidays and an additional day off for a birthday
• Summer working hours and flexible working arrangements
• Access to learning platforms, professional development courses and structured career progression
• Private medical insurance, healthcare support and mental health services
• Home workspace assessment to support a safe and productive working environment
• Paid volunteering days and opportunities to support charitable causes
• Access to car purchase, gym, technology and other lifestyle benefits

If you are an experienced Platform Engineer with strong Databricks and data platform engineering expertise, this is an excellent opportunity to contribute to modern cloud data solutions at scale.

Salary is negotiable but in the region of £80,000 plus bonus and other benefits. Skills

• Azure
• streaming
• Delta Lake
• Lakehouse
• Apache Spark
• Databricks
• Python
• SQL
• batch pipelines
• real-time pipelines

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• Significant experience building and supporting scalable, production-grade data platforms
• Strong hands-on expertise with Databricks, Apache Spark, Delta Lake, Python and SQL
• Good understanding of cloud-based data engineering, ideally within Microsoft Azure environments
• Experience with Infrastructure as Code tools such as Terraform, Bicep or similar
• Understanding of data modelling, ETL and ELT processes, data quality, security and governance
• Ability to collaborate effectively with technical and non-technical stakeholders
• Experience with Unity Catalog, MLflow or Databricks Asset Bundles would be advantageous
• Knowledge of dbt, Kafka, Event Hubs or other data transformation and streaming technologies would be beneficial

Desirable Experience:

• Databricks certifications
• Experience working with retail or consumer packaged goods data, including point-of-sale, inventory or supply chain datasets
• Understanding of modern data platform architecture and cloud engineering practices
• A degree in Computer Science, Data Engineering or a related discipline, or equivalent practical experience