Data Analyst

Job Description | Data Analyst Who are we? We are a fast-growing AI-first fintech platform enabling banks, NBFCs, and financial institutions to launch and scale next-generation credit products , including credit cards, credit lines, lending, and payment solutions. Our platforms process high-volume financial transactions and power business-critical customer journeys where reliability, performance, and security are non-negotiable. We are looking for a Data Analyst who thrives in high-ownership environments, enjoys solving complex engineering challenges, and is passionate about building products that directly impact millions of users and financial institutions. For more details, please visit https://falconfs.com/ (https://falconfs.com)
Job Summary:
We are looking for a Data Analyst with strong SQL, Python, Excel, and data visualization skills to support banking reports, credit card analytics, data reconciliation, and reporting. The candidate will analyse large datasets, ensure data accuracy, and build dashboards to support business decisions.
Key Responsibilities:

- Write and optimize SQL queries to extract, transform, and analyse large datasets.
- Use Python (pandas, NumPy) to clean, transform, and analyse data, and to build scripts for reconciliation and data validation.
- Prepare and validate banking, credit card, and regulatory reports.
- Identify data discrepancies, investigate root causes, and implement data quality checks.
- Build and maintain dashboards using Amazon Quick Sight, Tableau, or Power BI.
- Create ad hoc analyses and visualizations using Python libraries such as Matplotlib, Seaborn, or Plotly.
- Use Excel for data analysis, reconciliation, and reporting.
- Support automation of recurring reports and data processing workflows using Python.
- Collaborate with technical and business teams to clarify requirements and deliver reports on time.
- Document reporting logic, business rules, and validation procedures.
Required Skills & Qualifications:

- Bachelor’s degree in a relevant field.
- 2+ years of experience in data analytics, MIS reporting, or business intelligence.
- Strong SQL skills, including joins, CTEs, aggregations, and window functions.
- Good proficiency in Excel, including lookup functions, pivot tables, and data reconciliation.
- Hands-on Python scripting for data analysis and automation, including pandas and NumPy.
- Experience with Python visualization libraries such as Matplotlib, Seaborn, or Plotly.
- Hands-on experience with a data visualization tool: Amazon Quick Sight, Tableau, or Power BI.
- Strong analytical thinking, attention to detail, and problem-solving skills.
Good to Have:

- Exposure to AWS Athena, S3, and Lambda.
- Understanding of data quality checks, ETL processes, and reconciliation.