Enterprise Data Strategist

We are seeking a highly skilled and experienced Business Intelligence Analyst to play a pivotal role in our data transformation program. This position bridges the gap between complex business needs and technical data solutions, driving measurable impact on data quality, accessibility, and strategic decision-making.

Key Responsibilities:

• Data Analysis & Interpretation:
  • Gather, analyze, and translate complex business requirements related to data initiatives that support the enterprise-wide data transformation program.
  • 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 Visualization & 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.
• Process Design & Governance:
  • 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:

Education:

• 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.