Data Analyst

Vrinda Global; Dadri, Pune District, Bengaluru; Hybrid; INR 600,000 - 1,000,000; Full time

Job summary

Vrinda Global is seeking a Data Analyst to translate business problems into analytical solutions using SQL, Python and Spark across BFSI datasets. You will deliver insights and actionable recommendations to stakeholders and support data-driven decision making.

The role is hybrid with pan-India scope, requiring 4+ years of experience and strong analytical, data mapping and modeling skills to enable efficient business outcomes.

Qualifications

• 4+ years of professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills.

Responsibilities

• Convert business problems into analytical problems and propose solutions.
• Provide high-quality analysis and recommendations to business problems.
• Efficient project management and delivery.
• Conceptualize data-driven solutions for multiple businesses/regions to aid decision making.
• Drive efficiency gains and process improvements using data insights.
• Communicate status, risks and issues to stakeholders regularly.

Skills

SQL

Python

Pyspark

Hadoop

Hive

Spark

Data modeling

Education

Graduate in Computer Science / Data Science or related field

Tools

Hadoop

Hive

Spark

Spark SQL

Data mapping

Job description

Role: Data Analyst

Location: Pan India

Work Mode: Hybrid

Experience: 4+

Must-Have:

• 4+ 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(Preferred not mandatory).

• 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.