Build Python + Streamlit Dashboard for NinjaTrader Backtest Data (with Database Integration)

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I run ~30–40 NinjaTrader backtests per week across multiple time, tick, and volume charts (e.g., NQ 2500V, ES 1400T, ES 2min), with each backtest producing ~30–100 trades. I’m looking for a Python developer to build a system with these key components: Step 1 — Data Intake: • I run a backtest inside NinjaTrader and trigger (manual OK) a tool that pulls the backtest data. • The tool stores this data into an external database (PostgreSQL, SQLite, BigQuery, or recommend best option). • The data must retain the chart type/tag (e.g., NQ 2500V, ES 2min) either automatically or through a simple manual input field when importing. • Data should include longs, shorts, and combined rows for each chart. Step 2 — Analytics & Calculations: The system needs to calculate and display key performance summaries, including: • Weekly net profit: last 2 weeks (10 days) and 3 weeks (15 days) → positive or negative? • Monthly net profit: last 1 month (20 days) and last 2 months (40 days) → positive or negative? • Week-over-week profit direction → is it increasing? By how much? • Weekly win % → does it exceed the previous 5- or 10-week average? By what %? • Weekly number of trades → does it exceed the previous 5- or 10-week average? By what %? • Bonus: Any single day’s trade count exceeding the previous 10-day average? By what %? Step 3 — Dashboard Output: • Use Streamlit to build an interactive dashboard. • Provide visual cues (like green arrows, green text, or visual highlights) where performance signals are positive. • Make it easy to scan across multiple charts and quickly spot which ones are “heating up” or performing strongly. Deliverables: • Python scripts + Streamlit dashboard • Database setup + data pipeline • Clear documentation on how to run the tool after each backtest • Optional (but nice): recommendation on whether to use BigQuery, PostgreSQL, or another backend Budget & Timeline: Please submit your estimated cost and timeline. Include links to relevant Python/Streamlit/financial data projects you’ve worked on.

NinjaTrader Automation Python PostgreSQL SQLite BigQuery