About this role
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
Must-Have:
● 4-6 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
Graduate in Computer Science, Data Science, or related field. 2-3 years of experience in data engineering or related field.