Data Analyst

EXL; Pune District; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

EXL is looking for a data analyst in Pune, India with 4+ years of experience to drive data-driven decisions. The role requires strong analytical and problem-solving skills and hands-on work with SQL, PySpark and Python in a banking context (Credit & Lending).

You will work with Hadoop, Hive and Spark in data processing, mapping across multiple data sources, and contribute to data quality and modelling efforts within an Agile framework.

Qualifications

• 4+ years of professional experience as a Data Analyst with strong analytical and problem-solving skills.
• Proficiency in SQL, PySpark and Python with Banking domain knowledge (Credit & Lending).
• Working knowledge of Hadoop, Hive and Spark.
• Hands-on experience in Spark SQL / SQL for data exploration.
• Data mapping across sources and data asset design.
• Understanding of ER diagrams and data modelling concepts.
• Exposure to data quality validation and data cleaning.
• Experience with Agile methodologies.
• Knowledge of Basel II/III, IFRS 9 and Stress Testing advantageous.

Skills

SQL

PySpark

Python

Banking domain knowledge

Tools

Hadoop

Hive

Spark

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