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# Senior Platform Engineer (Databricks)

- **Company:** Retail Limited
- **Location:** Greater London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Microsoft Azure, Cloud Database, Information Engineering, Extract Transform Load (ETL), Data Transformation, Python (Programming Language), SQL Databases, Azure Service Bus, Apache Spark, Data Lakes, Infrastructure Automation Frameworks, Information Technology, Bicep, Apache Kafka, Data Management, Machine Learning Operations, Video Streaming, Terraform, Data Pipelines, Databricks
- **Published:** September 10, 2026
- **Apply:** https://www.collegerecruiter.com/job/2859576827-senior-platform-engineer-databricks

## About the Role

* Proven experience building and supporting scalable, production-grade data platforms.
 * Strong hands-on expertise with Databricks, Spark, Delta Lake, Python and SQL.
 * Good understanding of cloud-based data engineering, ideally within Azure environments.
 * Experience working with Infrastructure as Code tools such as Terraform, Bicep or similar.
 * Solid understanding of data modelling, ETL/ELT processes, data quality, security and governance.
 * Comfortable working with technical and non-technical stakeholders to deliver high-quality solutions., * Databricks certifications.
 * Experience with Unity Catalog, MLflow or Databricks Asset Bundles.
 * Familiarity with dbt or similar data transformation frameworks.
 * Exposure to Kafka, Event Hubs or other streaming technologies.
 * Experience working with retail or consumer packaged goods data, including point-of-sale, inventory or supply-chain datasets.
 * A degree in Computer Science, Data Engineering or a related discipline, or equivalent practical experience.

## Description

* Design, build and enhance our Databricks platform, ensuring it remains secure, scalable and reliable.
 * Develop and maintain batch and real-time data pipelines using Databricks, Spark and Delta Lake.
 * Contribute to platform architecture, engineering standards and best practices across the data estate.
 * Collaborate with Product, Analytics and Data Science teams to deliver solutions that solve real business problems.
 * Support platform operations, monitoring and optimisation to ensure high levels of performance and reliability.
 * Share knowledge with colleagues and help drive continuous improvement across the engineering team.


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