Ebay Reconciliation Data Analyst 

India, Karnataka, Bengaluru 

996144774

As a , you will work at the intersection of , and . You will be responsible for performing high-volume reconciliations and analysis between internal ledgers, payment pipelines, and banking partners. Additionally, you will apply to detect mismatches, predict anomalies, and support proactive financial risk management.

Reconciliation & Data Integrity

• Execute automated reconciliations between payment gateways, banking settlements, and internal transaction records.
• Maintain reconciliation SLAs (e.g., T+1, T+3 variance resolution) and build recon dashboards for daily break monitoring.
• Build and monitor dashboards for break detection, aging summaries, and resolution tracking.
• Use spark SQL queries and semi-structured data extraction for deep reconciliation pipelines.

Data Engineering & Automation

• Write scalable Hive/BigQuery queries to do RCA automation
• Build web tool using Python scripts to reduce manual work and data research.
• Develop and maintain recon tools and workflows using orchestration platforms (e.g., Airflow, DLS).
• Support pipeline enhancements by collaborating with engineering teams to optimize recon job performance.

Reporting & Audit

• Provide payment insights to support business decision and monitoring
• Present analysis findings and root cause summaries to finance controllers and auditors.
• Ensure data integrity in SOX-auditable recon processes; assist with documentation for internal controls.
• Support audit and compliance teams with automated variance tracking logs and break classification logic.

AI/ML-Driven Anomaly Detection & Forecasting

• Build lightweight ML models (e.g., classification, outlier detection) to provide issue summary, RCA of exception, payment data insight.
• Implement anomaly detection frameworks
• Work closely with data scientists and engineering to deploy detection pipelines within scheduled recon workflows.

Required:

• 4–7 years in data analytics, reconciliation, financial operations, or payments analytics
• Proficient in SQL , Hive/Presto , Python (Pandas, NumPy)
• Experience with Hadoop , Spark , or cloud-scale data platforms
• Ability to work independently with large-scale financial data systems
• Strong skill of Tableau or other BI tools

Preferred:

• Working knowledge of ML algorithms applied to anomaly detection or classification problems is plus
• Familiarity with financial data flows: settlements, payments, general ledger, etc.
• Understanding of ledger reconciliations, journal entries , and financial compliance