Business Intelligence Manager

The Business Intelligence Manager will play a crucial role in our data-driven decision-making process, bridging the gap between business needs and technical capabilities. This position will drive measurable impact on data quality, accessibility, and strategic decision-making.

This role requires a strong understanding of the insurance industry and a proven ability to navigate complex data landscapes.

Key Responsibilities:

• Translate business requirements into actionable data specifications, contributing to data modeling efforts, developing insightful analytics, and fostering strong cross-functional collaboration to ensure data initiatives align with our strategic objectives.
• 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.

Data Analysis & 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.

Qualifications:

• Bachelor's degree in Business Analytics, Information Systems, Computer Science, Statistics, Actuarial Science, or a related field.

Experience:

• 6+ years of experience as a data/business analyst working within insurance or financial services, with exposure to policy, claims, customer, or risk data.
• Industry Expertise:
• Strong understanding of insurance industry standards and regulatory requirements as they impact data capture, usage, and reporting (e.g., IFRS 17, Solvency II).
• Proven ability to apply domain expertise in the insurance industry.

Technical Skills:

• Advanced skills in SQL for data querying, profiling, and transformation.
• Proficiency in Power BI or similar BI tools for creating dashboards, reports, and visualizations.
• Experience translating business requirements into data requirements, mapping data flows, and defining user stories/specs for data engineering teams.

Stakeholder Management & Communication:

• Excellent communication skills (written and verbal) to work cross-functionally with business stakeholders, data engineers, architects, and governance teams.
• Strong facilitation skills for conducting workshops and managing cross-functional collaboration.
• Ability to translate complex technical concepts into clear, concise business language.

Analytical & Problem-Solving Skills:

• Strong analytical and problem-solving skills with a keen eye for detail.
• Ability to perform thorough data validation and identify data quality issues.

Good to Have Skills:

• Proficiency in logical and conceptual data modeling.
• Experience creating data flow diagrams, entity relationship diagrams (ERDs).
• Familiarity with data governance platforms and best practices, especially using Informatica for data cataloguing, metadata management, and lineage.
• Experience documenting data models, data dictionaries, and business glossaries.
• Experience with Spark (Databricks/Spark SQL) for data querying and transformation.