Website:
numerictalent.com
Job details:
We are looking for a Data Analyst with strong expertise in Python, ETL, and financial data handling to support our investment and wealth management team.
This role requires someone who can architect, design, and build end-to-end data pipelines from scratch, not just work on dashboards or reporting. The ideal candidate should have experience working with mutual funds, broking, or wealth management data and possess strong logical and mathematical thinking.
Responsibilities
- Architect, design, and implement end-to-end data pipelines for financial data
- Build and maintain ETL processes (Extract, Transform, Load)
- Process and transform investment datasets (portfolio, NAV, AUM, transactions, holdings)
- Import and automate Excel-based data workflows using Python
- Design and manage internal databases and data architecture
- Build and integrate APIs for seamless data flow
- Automate data pipelines and workflows for real-time or periodic updates
- Work closely with the investment team to deliver structured, reliable data
- Optimize and refactor large Python scripts and modular libraries
- Apply mathematical and logical transformations within the data layer
Qualifications
- Strong in Python (Pandas, NumPy, OpenPyXL)
- Solid understanding of ETL concepts (especially transformation logic)
- Experience in designing data pipelines / data architecture
- Strong in SQL & database design (PostgreSQL / MySQL / SQL Server)
- Experience with API development (FastAPI / Flask)
- Knowledge of data modeling & structuring
- Experience in automation & workflow design
- Basic understanding of Git/version control
Domain Expertise (Must Have):
- Wealth Management / AMC / Broking experience
- Understanding of portfolio data, NAV, AUM, holdings, investment datasets
- Experience 4+ years
Conceptual & Analytical Skills:
- Strong mathematical reasoning & logical thinking
- Expertise in data transformation & structuring
- Ability to handle complex and messy financial datasets
- Strong problem-solving mindset
Click on Apply to know more.