Job Description: Must-Have:

- 4+ / 5+ years of professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills.

- SQL, Pyspark, Python with Banking Domain knowledge - Credit & Lending.

Working knowledge / experience of Big Data frameworks like Hadoop, Hive and Spark.

- Hands-on experience in query languages like HQL or SQL (Spark SQL) for Data exploration.

- Data mapping: Determine the data mapping required to join multiple data sets together across multiple sources.

- Documentation - Data Mapping, Subsystem Design, Technical Design, Business Requirements.

- Exposure to Logical to Physical Mapping, Data Processing Flow to measure the consistency, etc.

- Data Asset design / build: Working with the data model / asset generation team to identify critical data elements and determine the mapping for reusable data assets.

- Understanding of ER Diagram and Data Modelling concepts

- Exposure to Data quality validation

- Exposure to Data Management, Data Cleaning and Data Preparation

- Exposure to Data Schema analysis.

- Exposure to working in Agile framework.

Knowledge of Credit Risk Frameworks such as Basel II, III, IFRS 9 and Stress Testing and understanding their drivers - advantageous

Responsibilities: Must-Have:

- 4-6 years of professional experience as a Data Analyst with positive decision-making,



analytical and problem-solving skills.

- SQL, Pyspark, Python with Banking Domain knowledge - Credit & Lending.

Working knowledge / experience of Big Data frameworks like Hadoop, Hive and Spark.

- Hands-on experience in query languages like HQL or SQL (Spark SQL) for Data exploration.

- Data mapping: Determine the data mapping required to join multiple data sets together across multiple sources.

- Documentation - Data Mapping, Subsystem Design, Technical Design, Business Requirements.

- Exposure to Logical to Physical Mapping, Data Processing Flow to measure the consistency, etc.

- Data Asset design / build: Working with the data model / asset generation team to identify critical data elements and determine the mapping for reusable data assets.

- Understanding of ER Diagram and Data Modelling concepts

- Exposure to Data quality validation

- Exposure to Data Management, Data Cleaning and Data Preparation

- Exposure to Data Schema analysis.

- Exposure to working in Agile framework.

Knowledge of Credit Risk Frameworks such as Basel II, III, IFRS 9 and Stress Testing and understanding their drivers - advantageous

Qualifications: Graduate in Computer Science, Data Science, or related field. 2-3 years of experience in data engineering or related field.

📌 Data Analyst (India)
🏢 EXL Service
📍 India