• We are looking for a Business Intelligence Analyst to turn collections and lending data into clear, decision-ready insight. You will own the reporting layer that sits between our raw data and our operational and executive stakeholders, building dashboards and analyses that drive recovery performance across our portfolio. This is a hands-on role for someone who is equally comfortable writing complex SQL and presenting a clean executive dashboard.

Roles and Responsibilities

• Design, build, and maintain BigQuery data models and queries supporting collections, recovery, and portfolio reporting.
• Develop and maintain Tableau dashboards covering DPD buckets, roll rates, RPC/PTP performance, recovery rates, campaign performance, and agent/team productivity.
• Partner with collections operations, finance, and leadership to translate business questions into scalable data products.
• Build and automate recurring reporting daily, fortnightly, monthly and reduce manual reporting effort.
• Investigate data quality issues, reconcile discrepancies across source systems dialer, CRM, core banking, ticketing, and ensure metric definitions are consistent and trusted.
• Monitor KPIs against targets, flag anomalies, and surface the “why” behind trends rather than just the numbers.
• Support experiments and initiatives e.g. cashback, campaign migrations, channel mix with measurement frameworks and impact analysis.

Requirements

• 8+ years in a BI, data analyst, or analytics engineering role, ideally within an NBFC, microfinance bank, fintech lender, or banking environment.
• Strong, demonstrable SQL skills on Google BigQuery CTEs, window functions, partitioning, query optimization, cost awareness.
• Proven expertise building production dashboards in Tableau LODs, calculated fields, parameters, performance tuning.
• Solid understanding of the collections and lending lifecycle: DPD buckets, roll rates, recovery and resolution metrics, PTP/RPC, write-offs, and portfolio risk.
• Ability to communicate findings clearly to both operational teams and senior leadership.

Nice to Haves

• Experience with dialer systems, CRM/ticketing platforms, and core banking or loan management systems.
• Familiarity with Metabase or other BI tools, and with cloud data warehousing concepts.
• Exposure to multi-market operations and the data complexity that comes with it.
• Awareness of data protection and governance requirements in financial services.