Data Modeler (Data Governance)

Develop and maintain conceptual, logical, and physical data models aligned with organisational data governance frameworks. Work with business stakeholders and data governance teams to ensure models support data accuracy, security, and regulatory compliance. Design data structures that promote consistency, accessibility, and reusability across systems. Collaborate with data governance teams, data stewards, and business units to define and enforce data standards and policies. Partner with data engineers, analysts, and database administrators to implement data models and ensure compliance with governance practices. Contribute to the development and maintenance of data dictionaries, metadata repositories, and data lineage documentation. Support the implementation of data quality metrics, monitoring, and reporting tools to align with governance objectives. Ensure that data models comply with organisational policies, industry standards, and regulatory requirements (e.g., GDPR). Advocate for data governance principles and best practices throughout the organisation. Evaluate and refine data models to optimise performance, scalability, and reliability. Identify and resolve data issues, including inconsistencies, redundancies, and security gaps. Provide guidance and training to stakeholders on the importance of data governance and how it is supported by effective data models. Act as a subject matter expert for data governance as it pertains to data modelling. 10+ years of experience in data architecture and modelling. Proven experience in data modelling, data architecture, and data products design. Proven experience and expertise in data modelling standards, techniques (e.g. dimensional model, 3NF, Vault 2.0) Familiarity with both analytical and real-time/ streaming data solutions. Hands-on experience with data modelling tools (e.g., Erwin, Lucidchart). Expertise in Python and SQL (e.g., Snowflake, Kafka). Experience in AWS cloud services, particularly Lambda, SNS, S3, and EKS, API Gateway Knowledge of data warehouse design, ETL/ ELT processes, and big data technologies (e.g., Snowflake, Spark). Hands-on experience with data governance frameworks, policies, and tools. Strong understanding of data quality principles, metadata management, and regulatory compliance requirements. Strong communication and stakeholder management skills. Analytical mindset with attention to detail. Ability to lead and mentor teams on best practices in data modelling. Education: Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. Certifications in data modelling, cloud platforms, or database technologies. Experience in developing and implementing enterprise data models. Certifications in data governance or data management (e.g., DAMA-CDMP, DGSP). Experience with Interface/ API data modelling. Experience with CI/CD GITHUB Actions (or similar) AWS fundamentals (e.g., AWS Certified Data Engineer) Knowledge of Snowflake/ SQL Knowledge of Apache Airflow Knowledge of DBT Familiarity with Atlan for data catalog and metadata management Understanding of iceberg tables