Research EXL before you apply
Check ratings, real-employee reviews, verified pay, and interview difficulty.
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.
Qualifications
Graduate in Computer Science, Data Science, or related field. 3-4 years of experience in data engineering or a related field.