Senior Data Analyst

EXL; Maharashtra; On-site; INR 800,000 - 1,200,000; Full time

Job summary

EXL in India is seeking a Data Analyst with 5+ years of professional experience, strong analytical and problem-solving skills, and solid SQL, PySpark and Python capabilities with Banking domain knowledge (Credit & Lending).

The role requires hands-on experience with big data frameworks like Hadoop, Hive and Spark, data mapping, data quality validation, data preparation, and working in Agile teams to deliver data-driven insights.

Qualifications

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

Skills

Decision making

Analytical skills

Problem solving

Tools

SQL

Pyspark

Python

Hadoop

Hive

Spark

Spark SQL

Job description

• 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.

Must-Have

• 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