Lead Assistant Manager

EXL Talent Acquisition Team; Pune District; On-site; INR 800,000 - 1,200,000; Full time

Job summary

EXL Talent Acquisition Team in Pune is seeking a Data Analyst with 5+ years of experience to drive data-driven decision making across banking domains, including credit and lending. Proficiency in SQL, PySpark and Python is required, along with hands-on experience in Hadoop, Hive and Spark for data exploration and mapping.

The role emphasizes data quality, data preparation, and documentation within an Agile environment to support data-driven initiatives across multiple sources.

Qualifications

• 5+ years of professional Data Analyst experience with strong analytical and problem-solving skills.
• Hands-on with SQL, PySpark, Python in banking domain (credit and lending).
• Experience with Hadoop, Hive and Spark big data frameworks.
• Experience in data mapping, data quality validation and data preparation.

Responsibilities

• Data mapping to join datasets across sources.
• Documentation of data mappings, subsystem and technical design.
• Data asset design and mapping with data model/asset teams.
• Understanding of ER diagrams and data modelling concepts.
• Exposure to data schema analysis and data quality validation.
• Work in an Agile framework.

Skills

SQL

PySpark

Python

Banking domain

Tools

Hadoop

Hive

Spark

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.
• 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