Senior Data Analyst

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.