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Partner Settlement Accountant
Job in
Lusail, Al Daayen, Qatar
Listed on 2026-06-07
Listing for:
ESP Engineered
Full Time
position Listed on 2026-06-07
Job specializations:
-
IT/Tech
Data Analyst -
Finance & Banking
Job Description & How to Apply Below
Our Partner Settlement Team lies at the core of Snoonu's financial success. We blend cutting edge technology, collaborative thinking, and a data driven approach to ensure our partners receive accurate, on time settlement. Embracing AI, automation, and cross functional partnerships, we continuously refine our operations to drive efficiency and innovation. We value curiosity, teamwork, and proactive problem solving, always striving to exceed expectations for both our partners and our internal stakeholders.
WhatYou'll Get Your Hands On
- Coordinate the on time cycles to ensure error free settlement.
- Develop settlement schedules and manage related communications to partners.
- Lead the daily and monthly reconciliation of partner accounts, comparing transactions between internal systems and bank statements.
- Investigate and resolve discrepancies, escalating issues to relevant stakeholders and ensuring smooth financial closure.
- Write and optimize SQL queries to pull, validate, and analyze large volumes of transaction data.
- Design and maintain data dashboards (using Excel, BI tools, etc.) that provide real time insights into settlement statuses, reconciliation progress, and KPIs.
- Implement best practices in database management to guarantee accuracy and reliability of financial records.
- Collaborate with IT teams to enhance data structures, ensuring high availability and scalability of settlement related data.
- Experience, 1+ years in settlements, financial operations, or reconciliation roles. Experience in e commerce or fintech is a plus.
- SQL & database expertise: skilled in SQL (query writing, optimization) and comfortable with database management tools. Data visualization (e.g., Power BI, Tableau) is a strong advantage.
- Analytical mindset: adept at digging into complex datasets, identifying patterns, and making data driven recommendations.
- Attention to detail: meticulous eye for spotting inconsistencies, ensuring a balanced approach to speed and accuracy.
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