Lead data Modeller/ Associate Lead Architect Lead Architect

To be successful in this role, you should meet the following requirements:

• Experience in cloud data solutions (e. g. , AWS, Azure, Google Cloud).
• Familiarity with big data technologies (e. g. , Hadoop, Spark).
• Knowledge of industry models (BIAN, FSDM, BDW etc. ) or experience in designing enterprise data models
• Leadership : You possess strong leadership skills, enabling you to support and inspire a team of Data Modellers. You can effectively communicate the strategic vision and guide the team towards achieving data modelling excellence.
• Data Modelling Expertise : You have a deep understanding of data modelling (for both operational and analytical systems), data analysis, metadata . You can elicit, document and verify requirements and translate them into scalable and efficient data models.
• Communication with Impact : Your communication skills are strong, allowing you to effectively convey complex data modelling concepts to both technical and non-technical stakeholders. You can influence and align stakeholders in getting the required signoffs.
• Consulting : You demonstrate strong consulting skills, leveraging your expertise to provide valuable insights and guidance to cross-functional teams. You can identify opportunities for improvement and drive data modelling excellence.
• Relationship/Stakeholder Management : You excel in managing relationships and stakeholders at various levels, establishing trust and collaboration to drive successful outcomes. You can effectively navigate and influence within a complex organisational structure.
• Problem Solving : Your problem-solving skills are expert level, enabling you to analyse complex data challenges and develop innovative solutions. You can guide the team in overcoming technical obstacles and making informed decisions.
• Data Governance : You have a strong understanding of data governance principles and can establish and enforce data governance frameworks, data quality standards, and data protection measures.