Data Architect

Role Overview

• Design and evolve scalable data models within a Databricks lakehouse architecture, structuring data across Bronze, Silver and Gold layers to support reporting and dashboard automation.
• Lead the design and implementation of data ingestion and transformation pipelines, working across structured and unstructured data sources to enable reliable, production-grade data flows.
• Act as a resident Data Architect on client site, working closely with stakeholders to understand requirements, shape data solutions, and ensure alignment to business outcomes.
• Engage with business and technical stakeholders to gather, refine and define data requirements, translating them into scalable and maintainable data architecture designs.
• Take ownership of the ongoing evolution of the data platform, continuously improving architecture, pipelines, and data structures in line with changing business needs.
• Lead and guide distributed delivery teams (onshore and offshore), ensuring consistent standards, clear direction, and successful execution of data initiatives.
• Establish and enforce best practices across data governance, lineage, metadata management, and data quality, ensuring trust and usability of data assets.
• Drive improvements in data processing performance, scalability, and cost optimisation, particularly within Databricks and distributed processing environments.
• Define and maintain data architecture standards, models, and documentation, ensuring consistency, reusability, and alignment across delivery teams.
• Support deployment and release processes, ensuring data solutions are robust, properly governed, and production-ready.

Requirements

• Bachelor’s or Master’s degree in IT, Computer Science, or a related field with significant experience (typically 8–10+ years) in data architecture, data warehousing, and large-scale data platforms, including hands-on experience in Databricks-led environments.
• Strong experience in enterprise data modelling across conceptual, logical, and physical layers, ideally within data lakehouse architectures (tools such as ERwin, ER/Studio, PowerDesigner or equivalent).
• Proven hands-on experience designing and supporting Databricks-based data platforms, including medallion architecture, Spark-based processing, and scalable data pipelines.
• Experience delivering data ingestion and transformation solutions (batch and streaming) using tools such as Databricks, Azure Data Factory (ADF), or similar modern data integration frameworks.
• Strong understanding of cloud-native data platforms (Azure preferred), including experience working with distributed data processing and integration with enterprise data stores (e.g., SQL Server, PostgreSQL, Oracle, Synapse).
• Familiarity with reporting and visualisation tools such as Power BI, Tableau, or similar.

Tech Stack

• Azure
• Cloud
• Oracle
• Postgres
• Spark
• SQL
• Tableau

Benefits

• A competitive salary with a generous bonus
• Private healthcare
• Life assurance at 4 x your annual salary
• Income protection insurance
• Rewarding pension
• Professional development opportunities