
Chief Data Strategist
18 hours ago
This is a highly coveted position that involves driving impactful data initiatives and fostering cross-functional collaboration.
Key Responsibilities:- Business Requirements & Data Analysis
- Gather, analyze, and translate complex business requirements related to data initiatives.
- Perform in-depth data profiling and gap analysis to identify data quality issues and opportunities for improvement.
- Translate business needs into clear data specifications, including KPIs, metrics, reporting requirements, and functional requirements documents for data solutions.
- Perform data validation to ensure accuracy, consistency, and integrity as part of the enterprise-wide data transformation initiative.
- Analytics & Reporting
- Develop and maintain dashboards, reports, and visualizations using tools such as Power BI (or similar BI tools) to support ongoing data quality monitoring and identify opportunities for continuous improvement.
- Utilize advanced SQL skills for data analysis, querying, profiling, and transformation, generating insights, and presenting findings to stakeholders.
- Translate technical concepts and data insights into clear, actionable business value for non-technical audiences.
- Stakeholder Management & Process Design
- Facilitate workshops and conduct user acceptance testing (UAT) for analytical or reporting solutions.
- Manage cross-functional collaboration with business stakeholders, data engineers, architects, and governance teams.
- Design and implement data governance processes that align with business objectives, ensuring transparency, traceability, and alignment across teams.
- Maintain and enhance data dictionaries, business processes, data flows, and business requirements.
- Project Execution & Domain Expertise
- Apply domain expertise in the insurance domain to ensure that industry-specific requirements are accurately captured and aligned with local regulatory standards (e.g., IFRS 17, Solvency II).
- Support project scrum execution by actively participating in sprint planning, daily stand-ups, and retrospectives, ensuring data-related tasks are clearly defined, prioritized, and delivered on time.
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