Assistant Manager - Business Analyst (Revenue & Operations)

Job Title: Business Analyst (Revenue & Operations)

Category: Business Location: Bengaluru, India

Role Overview

We are looking for a high-impact Business Analyst to serve as the data owner and guardian of

our bottom line. You will lead two critical areas: Refund Recoveryproactively reclaiming funds

from suppliers for unused servicesand Revenue Loggingtranslating complex commercial

contracts into system-wide tracking rules. This role is deeply operational, requiring constant

reconciliation and a detective mindset to ensure no revenue is left behind.

Key Responsibilities

Refund Recovery: Own the end-to-end reconciliation process to identify and reclaim

funds from suppliers for unused bookings within strict timelines.

Revenue Management: Translate new supplier deals and commercial contracts into

precise logic/rules to ensure 100% revenue tracking accuracy.

Operational Support: Be the primary data partner for the operations team, providing

them with daily actionable insights and Trip ID level highlights for recovery.

Data Automation: Design and maintain automated dashboards to track funnel health,

leakage points, and recovery performance.

Bottom-Line Protection: Conduct deep-dive audits to identify discrepancies between

system data and supplier reports.

Data Integrity: Partner with data engineering and product teams to ensure data accuracy,

implement new tracking measures, and maintain a robust data infrastructure.

Technical Skills & Qualifications

Expert SQL / BigQuery (BQ): You must be able to write complex joins and CTEs to

reconcile disparate datasets.

Advanced Excel: Mastery of XLOOKUP, Pivot Tables, and data cleaning for

high-volume reconciliation.

Visualization: Ability to build automated, self-service dashboards (Power BI, Tableau, or

Looker Studio).

Analytical Ownership: A hands-on approach to managing data end-to-end and a

commitment to daily operational excellence.

Analytical Thinking: Exceptional critical thinking and problem-solving skills, with the

ability to translate complex data into practical, business-focused insights.

Communication: Excellent written and verbal communication skills, with proven ability

to present complex data to non-technical audiences.

Attention to Detail: Meticulous attention to detail and a commitment to data accuracy.

Python (Preferred): Knowledge of Python (Pandas/NumPy) for automating repetitive

data pipelines and reporting is a strong plus.