Digital-first mortgage and savings bank with modern data infrastructure
Castle Trust Bank operates a low-cost banking model focused on mortgages, savings, and alternative lending. The tech stack reveals a data-driven organization—Power BI, SQL, Python, and Azure Synapse form the analytics backbone, with active adoption of Databricks and Unity Catalog signaling a shift toward unified data platforms. Current hiring focuses heavily on data (3 roles) and product (2 roles), underpinned by nine active projects centered on savings propositions, FP&A automation, and data governance—suggesting the bank is prioritizing product modernization and operational efficiency over pure growth.
Castle Trust Bank is a UK-based lender and savings provider founded in 2012, operating as a public company with 201–500 employees based in London. The bank targets two distinct customer segments: savings customers seeking FSCS-protected deposits, and mortgage borrowers—particularly buy-to-let investors and those with non-traditional income structures—who struggle with conventional lending criteria. The business model emphasizes minimal operational overhead and flexible underwriting. Core offerings include mortgages, buy-to-let lending, bridging finance, development loans, savings accounts, and consumer finance through the Omni Capital point-of-sale platform.
Power BI, Microsoft Office, Excel, Jira, Trello, SQL, Python, Azure DevOps, Azure Synapse, and Databricks. The bank is actively adopting Databricks and Unity Catalog as part of a next-generation data platform initiative.
Priority projects include new savings propositions, FP&A systems automation, scenario modelling, a next-generation data platform, Azure-Databricks evolution, SQL infrastructure, data governance improvement, and enhanced reporting solutions.
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