Data Strategy Advisor

As a Data Governance Lead at a Large Global Organization, you will play a crucial role in defining and advancing the CIM Data Governance roadmap. Your key responsibilities will include: - Defining and advancing the CIM Data Governance roadmap, encompassing data standardization, quality improvement, lineage, KPI harmonization, and reporting modernization. - Owning end-to-end delivery of governed data assets, involving deep data profiling, financial data analysis, and writing ETL transformation logic in Python. - Designing data models and standardized, governed data layers to facilitate reporting-ready datasets and semantic models. - Establishing and enforcing data definitions, lineage, naming conventions, and quality rules, and driving remediation and documentation practices. - Collaborating with Technology, Architecture, Engineering, BI, and Governance teams to ensure alignment and scalable implementation for long-term maintainability. Qualifications required for this role include: - 11 - 13 years of experience in finance/investment data, analytics engineering, BI, or data strategy. - Proficiency in ETL development and delivery of data pipelines for analytics and reporting. - Demonstrated data governance leadership skills, including standards, lineage, metadata, and quality rule enforcement. - Strong experience in Python for data transformations, validation, reconciliation, and documentation. - Finance domain knowledge to support investment/finance processes and ensure accurate reporting outputs. - Hands-on experience with Collibra for governance workflows, metadata management, and governed data handling. Additionally, the following skills would be considered advantageous: - Experience with Databricks for building and scaling data assets and transformation workflows. Education: - A relevant degree (or equivalent experience) in a quantitative field is required for this position. Join the team at this Large Global Organization and make a significant impact in the realm of data governance and finance data analytics. As a Data Governance Lead at a Large Global Organization, you will play a crucial role in defining and advancing the CIM Data Governance roadmap. Your key responsibilities will include: - Defining and advancing the CIM Data Governance roadmap, encompassing data standardization, quality improvement, lineage, KPI harmonization, and reporting modernization. - Owning end-to-end delivery of governed data assets, involving deep data profiling, financial data analysis, and writing ETL transformation logic in Python. - Designing data models and standardized, governed data layers to facilitate reporting-ready datasets and semantic models. - Establishing and enforcing data definitions, lineage, naming conventions, and quality rules, and driving remediation and documentation practices. - Collaborating with Technology, Architecture, Engineering, BI, and Governance teams to ensure alignment and scalable implementation for long-term maintainability. Qualifications required for this role include: - 11 - 13 years of experience in finance/investment data, analytics engineering, BI, or data strategy. - Proficiency in ETL development and delivery of data pipelines for analytics and reporting. - Demonstrated data governance leadership skills, including standards, lineage, metadata, and quality rule enforcement. - Strong experience in Python for data transformations, validation, reconciliation, and documentation. - Finance domain knowledge to support investment/finance processes and ensure accurate reporting outputs. - Hands-on experience with Collibra for governance workflows, metadata management, and governed data handling. Additionally, the following skills would be considered advantageous: - Experience with Databricks for building and scaling data assets and transformation workflows. Education: - A relevant degree (or equivalent experience) in a quantitative field is required for this position. Join the team at this Large Global Organization and make a significant impact in the realm of data governance and finance data analytics.