Strategy:
Create and maintain GPE data standards and guidelines that reflect the segment’s data strategy and risk tolerance; set GPE data priorities.
Partner with GPE Data Stewards, Product Owners, and Business subject matter experts to develop metrics/KPIs to measure the success of data governance activities.
Leverage data quality best practices to design and maintain policies, methodologies, guidelines around data quality, profiling, cleansing, including KPI/metrics definitions.
Deliver thought leadership for future data governance and management techniques and processes.
Data Governance:
Develop, document, manage, and provide oversight on data governance and data management policies, processes, standards, and procedures.
Mature the data governance program, securing engagement and buy-in for enterprise-wide data stewardship.
Accountable for maintaining standard terms and definitions for common data fields within the GPE segment.
Develop and implement data quality metrics, KPIs, and best practices.
Work with business and technology teams to implement a data catalog and data quality tools.
Design and drive a segment-wide education program on data governance and quality expectations.
Data Operations:
Lead Data Operations team and its data collection and governance processes to ensure data collected from portfolio companies and deal teams is consistent, accurate and timely. The Data Operations team will be responsible for:
Portfolio company onboarding onto the Chronograph platform, ensuring stakeholders have a clear understanding of the data to be submitted on a monthly and quarterly basis.
Data review and quality control, reviewing data submitted into Chronograph by the portfolio companies and/or deal team for completeness and accuracy.
Serving as the primary point of contact for portfolio companies, acting as the central communication hub for all data-related questions, issues, and escalations.
Administering tasks for newly acquired and exited portfolio companies.
Responsible for capacity planning, staffing, SLA definitions, and escalation paths with deal teams and portfolio companies.
Data Quality:
Define the scope and process to assess data quality, including identifying critical data, business rules, and data patterns.
Craft and perform an initial data quality assessment of critical data, identifying and prioritizing issues, and performing root cause analyses of issues.
Collaborate with cross-functional teams to identify, prioritize and manage data quality initiatives based on business impact.
Design and implement data quality dashboards and exception reports, performing analysis to identify trends in data quality issues, perform root-cause analysis, establish data quality themes, and determine course(s) of action, creating action plans to resolve open items.
Develop preventative and corrective actions to improve data quality and validation actions that can be implemented.
Manage and enforce data quality initiatives and standards, including data acquisition, enhancement, cleansing, and updating within and across application platforms.
Support and work with the business, data stewards, data custodians to remediate data quality exceptions.
Create and maintain GPE data standards and guidelines that reflect the segment’s data strategy and risk tolerance; set GPE data priorities.
Partner with GPE Data Stewards, Product Owners, and Business subject matter experts to develop metrics/KPIs to measure the success of data governance activities.
Leverage data quality best practices to design and maintain policies, methodologies, guidelines around data quality, profiling, cleansing, including KPI/metrics definitions.
Deliver thought leadership for future data governance and management techniques and processes.
Data Governance:
Develop, document, manage, and provide oversight on data governance and data management policies, processes, standards, and procedures.
Mature the data governance program, securing engagement and buy-in for enterprise-wide data stewardship.
Accountable for maintaining standard terms and definitions for common data fields within the GPE segment.
Develop and implement data quality metrics, KPIs, and best practices.
Work with business and technology teams to implement a data catalog and data quality tools.
Design and drive a segment-wide education program on data governance and quality expectations.
Data Operations:
Lead Data Operations team and its data collection and governance processes to ensure data collected from portfolio companies and deal teams is consistent, accurate and timely. The Data Operations team will be responsible for:
Portfolio company onboarding onto the Chronograph platform, ensuring stakeholders have a clear understanding of the data to be submitted on a monthly and quarterly basis.
Data review and quality control, reviewing data submitted into Chronograph by the portfolio companies and/or deal team for completeness and accuracy.
Serving as the primary point of contact for portfolio companies, acting as the central communication hub for all data-related questions, issues, and escalations.
Administering tasks for newly acquired and exited portfolio companies.
Responsible for capacity planning, staffing, SLA definitions, and escalation paths with deal teams and portfolio companies.
Data Quality:
Define the scope and process to assess data quality, including identifying critical data, business rules, and data patterns.
Craft and perform an initial data quality assessment of critical data, identifying and prioritizing issues, and performing root cause analyses of issues.
Collaborate with cross-functional teams to identify, prioritize and manage data quality initiatives based on business impact.
Design and implement data quality dashboards and exception reports, performing analysis to identify trends in data quality issues, perform root-cause analysis, establish data quality themes, and determine course(s) of action, creating action plans to resolve open items.
Develop preventative and corrective actions to improve data quality and validation actions that can be implemented.
Manage and enforce data quality initiatives and standards, including data acquisition, enhancement, cleansing, and updating within and across application platforms.
Support and work with the business, data stewards, data custodians to remediate data quality exceptions.