Lead Data Analyst

5+ yearsof 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. 3-4 years of experience in data engineering or a related field.

• 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.