ETL & Integration Architecture Design enterprise ETL frameworks and integration architectures. Develop data integration solutions using Informatica. Ensure reliable data movement between source and target systems. Implement data quality validation and reconciliation processes. Support real-time and batch integration strategies. Design and maintain conceptual, logical, and physical data models. Develop enterprise-wide data standards, naming conventions, and governance structures. Create scalable and reusable data architecture patterns. Maintain metadata repositories and data dictionaries. Ensure data consistency, integrity, and normalization across systems. Use ERWIN Data Modeller for enterprise modelling activities. Design dimensional models for enterprise reporting and analytics. Build star schemas, snowflake schemas, and OLAP cubes. Support BI and analytical platforms using: Essbase SQL Server Analysis Services (SSAS) Optimize analytical data structures for performance and scalability. Collaborate with BI developers and analysts to support reporting requirements. Experience 810 years in enterprise data modelling and architecture. Proven experience in large-scale enterprise environments. Strong experience in data warehouse design and implementation. Experience working with cross-functional technical teams.

Key Responsibilities The successful candidate will be responsible for: Designing, implementing and documenting data modelling solutions across relational, dimensional and NoSQL databases. Developing and maintaining conceptual, logical and physical data models in line with business and project requirements. Identifying and adopting enterprise data modelling standards to support best practice and accelerate modelling efforts. Supporting business data specialists with data modelling standards, methodologies, capacity and technical expertise. Monitoring, measuring and reporting on data modelling and data development quality levels. Ensuring business requirements are accurately reflected in data models and development outputs. Taking responsibility for the remediation of data model and data development issues. Performing reverse engineering of physical data models from databases and SQL scripts. Building and managing effective stakeholder relationships to promote data modelling awareness across the organisation. Minimum Requirements A Bachelors degree in Computer Science, Information Management or an equivalent qualification. 5 to 8 years experience in a data management environment. Experience in capacity and performance management. Extensive knowledge of data warehousing and multi-dimensional data modelling, including OLAP technologies such as ESSBASE or Microsoft Analysis Services . Strong knowledge of system design and data management principles. Extensive knowledge of data modelling techniques. Strong understanding of common RDBMS technologies such as Oracle, IBM, SQL Server and MySQL . Experience deploying or managing big data environments such as Hadoop, Spark and NoSQL . Knowledge of database query languages, particularly SQL . Experience with programming languages such as Java and C# . Experience using a broad variety of integration techniques, patterns, tools and methodologies. Advantageous Skills and Certifications Certification or experience in any of the following will be advantageous: AWS Informatica Tool Stack SAS ERWIN Python R Teradata This is an opportunity to work on a strategic transformation programme where data plays a central role in shaping business capability. You will work closely with business and technical stakeholders, contribute to enterprise data standards, and help build a data environment that supports long-term organisational success.