BI & Data Operations Specialist – Mobile Installment (BNPL) at PalmPay

Job Summary

• The BI & Data Operations Specialist will play a vital role in driving data-driven decision-making within Flexi MFB’s Mobile Installment business.
• The role involves managing data pipelines, ensuring data accuracy, developing performance dashboards, and providing actionable insights that support strategic and operational objectives across credit, collections, merchant operations, and customer engagement.
• This individual will collaborate closely with product, finance, operations, and technology teams to ensure data quality, enhance reporting efficiency, and deliver business intelligence that drives growth, profitability, and operational excellence.

Key Responsibilities
Data Management & Operations:

• Manage end-to-end data flow across systems supporting the Mobile Installment business (loan origination, repayment, merchant management, CRM, etc.).
• Ensure data integrity, consistency, and reliability across multiple data sources and platforms.
• Collaborate with Tech teams to identify and fix data discrepancies, integration errors, or system mismatches.
• Design and maintain SQL scripts, ETL processes, and data pipelines to automate recurring reports and dashboards.

Business Intelligence & Reporting:

• Develop and maintain BI dashboards and performance reports to monitor business metrics such as loan disbursements, repayments, NPL ratios, merchant activity, and collection performance.
• Provide insights and trend analysis to support decision-making by management and stakeholders.
• Visualize data effectively using BI tools such as Power BI, Tableau, or Google Data Studio.
• Translate business requirements into technical specifications for BI solutions.

Data Analysis & Insights:

• Perform deep-dive analyses on credit performance, customer repayment behavior, and merchant transaction trends.
• Identify key performance drivers, risks, and opportunities within the BNPL portfolio.
• Support forecasting, risk modeling, and portfolio optimization initiatives using historical data.
• Collaborate with finance and operations to reconcile data used in financial and operational reporting.

Performance Monitoring & Optimization:

• Track and evaluate product and business KPIs, including disbursement trends, approval rates, default rates, and collection efficiency.
• Identify operational inefficiencies and recommend data-backed solutions.
• Support the product team with pre-launch and post-launch data insights for new features or campaigns.

Collaboration & Stakeholder Support:

• Partner with Credit, Collections, Merchant Operations, and Product teams to deliver customized reports and insights.
• Present data findings to both technical and non-technical stakeholders clearly and concisely.
• Contribute to cross-functional business reviews, providing data insights to support strategy formulation.

Compliance & Data Governance:

• Ensure compliance with internal data policies, data privacy regulations, and CBN/NITDA standards.
• Maintain documentation of data sources, processes, and BI reports.
• Support audit requirements by providing accurate and traceable data reports.

Key Performance Indicators (KPIs)

• Data accuracy and integrity across all systems.
• Timeliness and quality of reports delivered.
• Adoption and utilization rate of BI dashboards by business users.
• Efficiency in identifying and resolving data issues.
• Quality of insights driving business decisions.

Key Requirements
Education & Experience:

• Bachelor’s Degree in Statistics, Computer Science, Economics, Finance, Engineering, or related field.
• 3–5 years of experience in Data Analysis, BI, or Data Operations within fintech, digital lending, banking, or consumer finance sectors.
• Strong proficiency in SQL, Excel, and BI visualization tools (Power BI, Tableau, or equivalent).
• Experience with data pipeline management (ETL tools, APIs, or data warehouse systems).
• Prior exposure to credit analytics, lending performance tracking, or BNPL operations preferred.

Skills & Competencies:

• Strong analytical and quantitative reasoning abilities.
• Deep understanding of data modeling, relational databases, and data governance best practices.
• Proficiency in Python or R (for advanced analytics) is an added advantage.
• Excellent communication and presentation skills.
• Attention to detail, accuracy, and strong problem-solving mindset.
• Ability to work collaboratively in a fast-paced and dynamic environment.