Data Quality Lead at Jubilee Insurance

Role Purpose

The role holder will be responsible for assessing, monitoring, and improving data quality standards and processes to support informed decision-making, regulatory compliance, and operational efficiency. He/ She will ensure the accuracy, completeness, and integrity of data assets.

Main Responsibilities
Operational

• Data Quality Assessment: Conduct regular audits and assessments of data quality across various systems and sources, identifying inconsistencies, errors, and gaps in data integrity.
• Data Profiling: Analyse data sets to understand data patterns, anomalies, and relationships, identifying potential issues and areas for improvement in data quality.
• Root Cause Analysis: Investigate data quality issues to determine underlying causes, collaborating with relevant stakeholders to implement corrective actions and preventive measures.
• Data Cleansing: Develop and implement data cleansing procedures and workflows to address data quality issues, ensuring the accuracy and completeness of data records.
• Quality Metrics Monitoring: Define and monitor key performance indicators (KPIs) and quality metrics to track data quality trends, progress, and compliance with established standards. 
• Master Data Management (MDM): Drive the implementation of MDM, ensuring consistency and quality of master data across all business units. Develop processes for data entry, validation, and remediation within the MDM framework.
• Documentation and Reporting: Maintain documentation of data quality rules, processes, and remediation efforts, preparing regular reports and presentations to communicate findings and recommendations to stakeholders.
• Process Improvement: Identify opportunities to enhance data quality processes, tools, and controls, collaborating with cross-functional teams to implement best practices and continuous improvement initiatives.
• Training and Awareness: Provide training and support to end-users on data quality best practices, tools, and procedures, fostering a culture of data stewardship and accountability within the organization

Corporate Governance

• Ensure adherence to the laws and regulations of Kenya and all internal company policies and procedures.
• Ensuring compliance with applicable statutory and regulatory requirements and establishing mitigation measures against emerging business risks.

People & Culture

• Fostering a corporate culture that promotes ethical practices and good corporate citizenship while maintaining a conducive work environment.
• Collaborate with cross-functional teams to develop initiatives that promote a positive and inclusive company culture.
• Individualized Development Planning: Create personalized development plans that align with your career aspirations and the organization's objectives.

Key Deliverables

• Conduct data quality assessments and prepare audit reports.
• Data quality improvement plans and remediation strategies.
• Documentation of data quality rules and processes.
• Monitoring reports on key performance indicators (KPIs) and quality metrics

Key Competencies

• Technical skills: Strong experience in SQL, Python, and Power BI.
• Analytical Thinking: Ability to Analyze complex data sets and identify patterns, trends, and anomalies.
• Problem-Solving: Proficiency in identifying root causes of data quality issues and developing effective solutions.
• Attention to Detail: Thoroughness in ensuring data accuracy, completeness, and consistency.
• Communication Skills: Clear and effective communication of findings, recommendations, and status updates to stakeholders.
• Collaboration: Ability to work collaboratively with cross-functional teams to address data quality challenges and implement improvements.

Relevant Qualifications and Experience

• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related field from a recognized institution.
• Relevant certification such as CDMP, CDGP or CIGO is a plus.
• 3+ years of experience in data quality or related roles, with experience in multi-cloud environments (Azure, Oracle OCI).
• Hands-on experience with data governance tools such as Microsoft Purview, Compliance Manager, Profisee, Informatica MDM, SAP MDG.
• Strong with SQL and Python for data mining.