
1001 - 5000 employees
🤖 Artificial Intelligence
🔒 Cybersecurity
💰 Private Equity Round on 2019-01
Artificial Intelligence • Consulting • Cybersecurity
Brillio is a technology consulting company that specializes in driving digital transformation for businesses across various industries such as banking, financial services, insurance, life sciences, telecom and media, healthcare, and retail. They focus on customer experience transformation, data and AI, product and platform engineering, and provide infrastructure, cloud, and security solutions. With an emphasis on engineering digital products and leveraging generative AI, Brillio aims to provide bespoke solutions that help businesses thrive in the age of AI and technological disruption. They also offer services to help businesses adapt to new technological challenges and turn disruptions into competitive advantages.
🕒 March 4
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1001 - 5000 employees
🤖 Artificial Intelligence
🔒 Cybersecurity
💰 Private Equity Round on 2019-01
Artificial Intelligence • Consulting • Cybersecurity
Brillio is a technology consulting company that specializes in driving digital transformation for businesses across various industries such as banking, financial services, insurance, life sciences, telecom and media, healthcare, and retail. They focus on customer experience transformation, data and AI, product and platform engineering, and provide infrastructure, cloud, and security solutions. With an emphasis on engineering digital products and leveraging generative AI, Brillio aims to provide bespoke solutions that help businesses thrive in the age of AI and technological disruption. They also offer services to help businesses adapt to new technological challenges and turn disruptions into competitive advantages.
• Take full ownership of the data modelling lifecycle, from requirements gathering through to deployment and ongoing maintenance. • Design, develop, and maintain logical and physical data models, primarily using Databricks and the Nova platform. • Ensure data models are aligned with business requirements, data governance standards, and best practices. • Collaborate with data engineers, architects, and business stakeholders to understand data requirements and translate them into effective data structures. • Document data models, definitions, and metadata to ensure clarity and consistency across the organisation. • Review and optimise existing data models for performance, scalability, and maintainability. • Lead model validation and quality assurance activities, ensuring models are accurate and fit for purpose. • Provide guidance and support to project teams and business users on data modelling best practices. • Act as the primary point of contact and subject matter expert for all matters relating to data models within your area of responsibility. • Champion data model governance and ensure models are maintained in line with organisational standards and policies. • Support the integration of new data sources and the evolution of the enterprise data platform.
• Extensive experience in data modelling, including both logical and physical modelling, ideally within Databricks and/or similar cloud-based platforms. • Demonstrable experience of owning and maintaining enterprise data models, including responsibility for model governance and documentation. • Strong understanding of data warehousing, lakehouse architectures, and modern data platforms. • Ability to translate complex business requirements into scalable and efficient data models. • Proficient in data modelling tools and techniques, with hands-on experience in Databricks and the Nova platform (or similar). • Excellent communication skills, with the ability to work collaboratively across technical and business teams. • Experience in data governance, metadata management, and data quality assurance. • Strong analytical and problem-solving skills. • Desirable • Experience working in regulated industries such as insurance or financial services. • Familiarity with reporting requirements such as IFRS and Solvency II. • Experience with data visualisation tools and supporting analytics/reporting teams. • Knowledge of automation tools and scripting for data model management. • Experience working in Agile product teams and using tools such as JIRA/Confluence.
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