Senior Data Analyst

Job description

**Job Description: 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. Qualifications: Graduate in Computer Science, Data Science, or related field. 2-3 years of experience in data engineering or related field.