Senior Data Analyst

Job Description Summary :

Key Skills : Strong SQL, Python, Pyspark, Jupyter Notebook, Agile / Scrum / Jira / Confluence, Microsoft Excel, Exposure to any cloud (GCP / AWS / Azure) would be a plus

Job Description :

Must-Have :

- 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 Modeling 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.

- SQL, Pyspark, Python with Banking Domain knowledge / Credit & Lending domain knowledge.

- Knowledge of Credit Risk Frameworks such as Basel II, III, IFRS 9 and Stress Testing and understanding their drivers advantageous

- Retail Credit / Traded Credit knowledge - applications will be considered

Good To Have :

- Data Visualization - Tableau or Qlik Sense

- Exposure to Hadoop, Hive and ETL.

- Working knowledge of any cloud services like AWS or GCP or Azure.

- Any relevant certifications would be a plus.

Role & Responsibilities :

- 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.

- Follow the processes for project execution and delivery.

- Follow agile methodology.

- 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.