Credit Risk Data Analyst –SQL, Python & PySpark Experience: 3–7 Years Location: Bangalore Notice - Immediate to 15 Days Role Summary Seeking a Credit Risk Data Analyst with robust hands-on expertise in Python and PySpark to support large-scale data processing, validation, and analytics across credit risk datasets. The role focuses on leveraging distributed data frameworks to ensure data accuracy, scalability, and effective processing within contemporary data platforms.

Key Responsibilities - Perform large-scale data processing, transformation, and validation using Python and PySpark
Build and optimize data pipelines for ingestion, processing, and analysis of credit risk datasets
Conduct exploratory data analysis (EDA), anomaly detection, and trend identification
Implement data quality checks covering accuracy, completeness, and consistency
Perform data reconciliation and support data migration validation activities
Work with distributed data environments (e.g., big data platforms)



to handle high-volume datasets
Collaborate with stakeholders to understand business requirements and data flows
Assist in preparing and validating datasets used in PD, LGD, and EAD models
Partner with data engineering and risk teams to improve data processing efficiency - Required Skills - Strong hands-on experience in Python and PySpark
Experience in building and optimizing data pipelines in distributed settings
Solid understanding of data transformation, validation, and big data processing
Exposure to data quality frameworks and governance practices Domain Requirements (Uniform Across JDs) - Strong understanding of Credit Risk fundamentals
Exposure to PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default) models
Knowledge of retail banking portfolios such as loans, cards, and mortgages

📌 Credit Risk Data Analyst Bengaluru
🏢 Etenico Technologies
📍 Bengaluru