Data Analyst - ETL/Python

About The Job

About Snapmint

Snapmint is a leading fintech company redefining access to consumer credit in India.

With over 10 million customers across 2,200+ cities, our zero-cost EMI platform enables responsible purchases without the need for a credit card across categories like fashion, electronics, and lifestyle.

India has over 300 million credit-eligible consumers, yet fewer than 35 million actively use credit cards.

Snapmint addresses this gap by offering a trusted, transparent alternative grounded in financial inclusion and ethical lending practices.

Founded in 2017, Snapmint is a profitable, high-growth company doubling year-on-year.

Our founding team alumni of IIT Bombay and ISB brings deep experience from Oyo, Ola, Maruti Suzuki, and prior successful ventures in ad-tech, patent analytics, and bank-tech.

We are building the future of responsible consumer finance simple, transparent, and customer-first.

Key Responsibilities

• Extract, clean, and analyze data using SQL and Python for internal and external reporting.
• Prepare, validate, and submit credit bureau data files (e.g., Equifax, Experian, TransUnion) in
  
  

accordance with bureau formats and timelines.

• Perform data quality checks to ensure completeness, accuracy, and consistency before submission.
• Collaborate with compliance, credit, and engineering teams to resolve data discrepancies or logic issues in reporting.
• Maintain documentation of reporting processes, validation rules, and submission logs.
• Automate repetitive data preparation and validation processes where possible.
• Monitor bureau feedback and rejection reports; lead root-cause analysis and remediation.
• Support internal audits, regulatory exams, and data governance initiatives related to bureau reporting.
  
  

Required Qualifications

• Bachelor's degree in Computer Science, Data Analytics, Statistics, Finance, or a related field.
• 2-3 years of experience in Fintech/ NBFC
• Proficient in SQL ability to write complex queries and handle large datasets.
• Experience in Python for data wrangling, validation, and automation (e.g., using pandas, NumPy).
• Prior experience in preparing credit bureau submissions or working with consumer credit data.
• Strong attention to detail and analytical thinking.
• Familiarity with data validation frameworks and reporting standards.
• Good communication skills and the ability to collaborate with cross-functional teams
  
  

(ref:hirist.tech)