Data Analyst
Web Spiders (company site, opens in a new tab)1–3 yrsKolkataOn-siteDirect career pageEst. 4–8 LPA
Posted on 24 Sept
Reach people at Web Spiders
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Web Spiders you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Analyze US consumer credit card spend data to research, classify, and map brands and merchants for accurate insights and analytical reporting.
- Build and maintain data pipelines using Python and SQL to transform raw transaction data into analysis-ready datasets, collaborating with senior engineers and data scientists.
- Produce clear analytical reports, support data workflow development and monitoring on AWS services, and ensure data quality with checks and reconciliation routines.
Minimum Requirements
- 1 to 3 years of professional experience in data analysis, data engineering, market research, or closely related role.
- Strong proficiency in Python (production-quality scripting) and SQL including complex queries and optimization.
- Mandatory working knowledge of regular expressions and AWS services (S3, Glue, Athena, Redshift).
- Graduate degree required; working knowledge of ETL/ELT concepts, data modeling, Git, and AI-assisted coding tools.
Ideal Candidate Profile
- Comfortable working with US Eastern time zone hours or hybrid half IST/half EST based on project needs.
- Experienced in detailed online research and able to resolve ambiguous data records through unconventional information sources.
- Capable of delivering well-documented, high-standard classification and data engineering work with client communication skills.