Python Developer for Real-Time Dashboard

Project Overview:
We are looking for an experienced Python developer to build a lightweight, real-time web-based dashboard and data processing pipeline for ~210 NSE F&O stocks. The system will ingest live market data via Angel One SmartAPI, maintain a 1-day rolling historical cache of intraday candles, execute custom indicator logic in a modular calculation engine, and render the processed data in an interactive table dashboard.

1. Data Pipeline & Backend Architecture:
- Data Ingestion: Connect to Angel One SmartAPI WebSocket V2 to stream live real-time tick/candle data for ~210 NSE F&O underlying stock symbols during market hours.
- Historical Data Seeding: Seed 1-minute and 5-minute historical OHLC candle data at startup via the historical REST API endpoint.
- Local Data Caching: Store a 1-day rolling history of 1-minute and 5-minute OHLC candles using a high-performance local cache/database (e.g., Redis or SQLite).
- Timeframe Aggregation: Handle 1-minute candle close updates for Metric A and 5-minute candle close updates for Metric B.

2. Isolated Calculation Engine (Crucial Requirement):
- Create a modular Python file (e.g., indicators.py) with execution hooks for metric calculations.
- The engine must pass the respective symbol dataframes:
* Metric A Function: Passed 1-minute OHLC dataframe (returns 1-min candle close for testing).
* Metric B Function: Passed 5-minute OHLC dataframe (returns 5-min candle close for testing).
- The system MUST allow us to edit or replace internal mathematical formulas inside indicators.py in the future without modifying the database pipeline or UI structure.

3. Frontend Web Dashboard (Streamlit / Dash / FastAPI + Vue/HTML):
- Header Summary Cards:
* Total Tracked F&O Stocks (Count)
* Total Gainers Count (% Change > 0)
* Total Losers Count (% Change < 0)
- Main Interactive Data Table:
* Required Columns: Sr No | Stock Symbol | % Change | Metric A | Metric B
* View Filters / Tabs: All Stocks | Gainers Only (% Change > 0) | Losers Only (% Change < 0)
* Features: Real-time column sorting (ascending/descending on all columns) and an instant live search/filter bar for stock symbols.

4. Deliverables:
- Complete Python source code repository with clean documentation and environment configuration (.env template).
- Backend service script, database setup, and frontend launcher.

Required Skills:
- Python (Pandas, NumPy, Asyncio/WebSockets)
- Stock Broker APIs (Angel One SmartAPI, Zerodha Kite, or Fyers)
- Redis / SQLite database caching
- Frontend UI frameworks (Streamlit, Dash, or HTML/JS)

Budget & Timeline:
- Type: Fixed Price
- Expected Delivery: 3 to 5 Days