Lead Assistant Manager

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 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.