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
Responsibilities- Ability to convert business problem to an analytical problem and then finding pertinent solutions
- Overall business understanding of BFSI domain
- Providing high-quality analysis and recommendations to business problems.
- Efficient project management and delivery
- Ability to conceptualize data driven solutions for the business problem at hand for multiple businesses/region to facilitate efficient decision making
- Focus on driving efficiency gains and enhancement of processes.
- Use of data to improve customer outcomes through the provision of insight and challenge
● Understand the business requirements from the product/project stakeholders and break the requirements into simpler stories and tasks and do the necessary mapping of the tasks to the logical model of the solutions.
● Mapping of business entities to technical attributes with the logic for transformation defined clearly.
● Be accountable for the delivery of the tasks in the defined timelines with good quality.
● Working with the team leads closely and contribute to the smooth delivery of the project.
● Understand/define the architecture and discuss the pros-cons of the same with the team.
● Involve in the brainstorming sessions and suggest improvements in the architecture/design.
● Working with other teams leads to getting the architecture/design reviewed.
● Keep all the stakeholders updated about the project, task status, risks, and issues if any.
QualificationsGraduate in Computer Science, Data Science, or related field. 2-3 years of experience in data engineering or related field.
Skills Required
- 5+ years professional experience as a Data Analyst
- Proficiency in SQL
- Proficiency in PySpark
- Proficiency in Python
- Banking domain knowledge - Credit & Lending
- Working knowledge/experience with Hadoop
- Working knowledge/experience with Hive
- Working knowledge/experience with Spark
- Hands-on experience with HQL or Spark SQL for data exploration
- Data mapping across multiple sources and data sets
- Documentation of Data Mapping, Subsystem Design, Technical Design, Business Requirements
- Exposure to logical-to-physical mapping and data processing flow consistency
- Experience designing/building data assets and mapping critical data elements
- Understanding of ER diagrams and data modeling concepts
- Exposure to data quality validation
- Experience with data management, cleaning, and preparation
- Exposure to data schema analysis
- Experience working in an Agile framework
- Graduate in Computer Science, Data Science, or related field
- 2-3 years experience in data engineering or related field
- Knowledge of Credit Risk Frameworks (Basel II/III, IFRS 9, Stress Testing)
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
