About the role : Primary function of the role is to deliver high quality data engineering solutions to business and end users across Asset Lending (Asset Finance, Working Capital and Asset Based Lending businesses either directly via self-service data products, or by working closely with the Analytics team, providing modelled data warehouses on which they can add reporting and analytics. Reporting to the Head of ccc Technology, this role will fill a crucial role in bridging the gap between business needs, the requirements from the data analytics team and translating these into engineering delivery. Key Responsibilities : Work closely with end-users and Data Analysts to understand the business and their data requirements Carry out ad hoc data analysis and data wrangling using Synapse Analytics and Databricks Building dynamic meta-data driven data ingestion patterns using Azure Data Factory and Databricks Build and maintain the Enterprise Data Warehouse (using Data Vault 2.0 methodology) Build and maintain business focused data products and data marts Build and maintain Azure Analysis Services databases and cubes Share support and operational duties within the wider engineering and data teams Work with Architecture and Engineering teams to deliver on these projects. and ensure that supporting code and infrastructure follows best practices outlined by these teams. Help define test criteria to establish clear conditions for success and ensure alignment with business objectives. Manage their user stories and acceptance criteria through to production into day-to-day support Assist in the testing and validation of new requirements and processes to ensure they meet business need What are we looking for? Excellent data analysis and exploration using T-SQL Strong SQL programming (stored procedures, functions) Extensive experience with SQL Server and SSIS Knowledge and experience of data warehouse modelling methodologies (Kimball, dimensional modelling, Data Vault 2.0) Experience in Azure one or more of the following: Data Factory, Databricks, Synapse Analytics, ADLS Gen2 Experience in building robust and performant ETL processes Build and maintain Analysis Services databases and cubes (both multidimensional and tabular) Experience in using source control & ADO Understanding and experience of deployment pipelines

The Offshore Data Engineering Lead will be responsible for overseeing the data and application development efforts which support our Microsoft Data Mesh Platform. Working as a part of the Investec Central Data Team, the candidate will be responsible for leading development on solutions and applications that support our data domain teams with creation of data products. This role involves driving technical initiatives, exploring new technologies, and enhancing engineering practices within the data teams in-line with the group engineering strategy. The Data Engineering Lead will be a key driver for Investecs move to Microsoft Fabric and other enablement data quality, data management and data orchestration technologies. Key Roles and Responsibilities: Lead the development and implementation of data and custom application solutions that support the creation of data products across various data domains. Design, build, and maintain data pipelines using Microsoft Azure Data Platform, Microsoft Fabric and Databricks technologies. Ensure data quality, integrity, and security within the data mesh architecture. Share group engineering context with the CIO and engineers within the business unit continuously. Drive engineering efficiency and enable teams to deliver high-quality software quickly within the business unit Cultivate a culture focused on security, risk management, and best practices in engineering Actively engage with the data domain teams, business units and wider engineering community to promote knowledge sharing Spearhead technical projects and innovation within the business units engineering teams and contribute to group engineering initiatives Advance the technical skills of the engineering community and mentor engineers within the business unit Enhance the stability, performance, and security of the business units systems. Develop and promote exceptional engineering documentation and practices Build a culture of development and mentorship within the central data team Provide guidance on technology and engineering practices Actively encourages creating Investec open-source software where appropriate within the business unit Actively encourages team members within the business unit to speak at technical conferences based on the work being done Core Skills and Knowledge: Proven experience in data engineering, with a strong focus on Microsoft Data Platform technologies, including Azure Data Factory, Azure SQL Database, and Databricks Proficiency in programming languages such as C# and/or Python, with experience in application development being a plus Experience with CI/CD pipelines, Azure, and Azure DevOps Strong experience and knowledge with PySpark and SQL with the ability to create solutions using Microsoft Fabric Ability to create solutions that query and work with web APIs In-depth knowledge of Azure, containerisation, and Kubernetes Strong understanding of data architecture concepts, particularly data mesh principles Excellent problem-solving skills and the ability to work independently as a self-starter Strong communication and collaboration skills, with the ability to work effectively in a remote team environment Relevant degree in Computer Science, Data Engineering, or a related field is preferred