Sr. Backend Developer (Algorithmic Trading, Python) - Part-time - Worldwide

Role Overview

We’re seeking an Advanced Back-End Developer (Algorithmic Trading, Python) to build and harden a low-latency auto-execution system for a Morning Momentum Dip-Buy strategy. You’ll implement real-time scanning, broker API execution, and a configurable dashboard to manage entry/exit rules, risk, and session controls (runs 6:45–10:15am ET).

Responsibilities

• Build real-time scanners (gap/RVOL/float/mkt-cap/price) and track HOD to detect the first pullback only.
• Implement scaled limit entries at configurable %-from-HOD levels; cancel on bounce; reject if new HOD forms pre-fill.
• Integrate broker/data APIs (e.g., DAS Trader, IBKR, Sterling/Lightspeed) with OCO/brackets, cancel/replace, flatten/kill-switch.
• Enforce risk & exits: avg-cost stop-loss, tiered profit targets, post-target trailing stop, single-pass ticker lockout.
• Deliver a control dashboard (web or desktop) with configurable inputs, start/stop, cancel all, flatten, and live P&L/positions.
• Log trades/configs; export CSV/Excel/JSON; add structured logging and basic metrics.
• Backtest/paper-trade; write unit/integration tests; handle halts, disconnects, symbol changes gracefully.

Required Skills

• Python 3.11+ with Pandas/NumPy, asyncio, type hints; event-driven, low-latency pipelines (ms-level).
• Streaming ingestion (WebSockets) with robust reconnects/heartbeats; concurrency (async tasks/queues).
• Broker & market data APIs: DAS Trader, IBKR, Sterling/Lightspeed (orders, OCO/brackets, partial fills, cancels).
• Strategy mechanics: HOD tracking; first-pullback logic; dashboard-configurable gap% band (e.g., 25–75%) and 45-day “similar move” cooldown filtering in the scanner.
• Risk & execution: scaled entries, cancel-on-bounce, no averaging beyond plan, avg-cost stop, tiered targets, trailing stop.
• Dashboard/UI: React + FastAPI/Flask (web) or PyQt/Electron (desktop) for real-time control panels.
• Data & storage: SQLite/Postgres for logs/configs; exports (CSV/Excel/JSON); audit trails.
• Testing/QA: pytest (mocks for broker/data), backtesting & paper trading, resilience to halts/disconnects.
• Engineering hygiene: Git, code review, typing/linting (mypy/ruff/black), profiling, secrets management.
• Domain & collaboration: day-trading concepts; clear written updates to non-technical managers; NDA; 1–2 hrs daily ET overlap.

Nice to Have

• C++ for hot paths; Level-2/tape & microstructure familiarity; latency budgeting.
• Docker and simple CI (GitHub Actions); basic cloud (AWS/GCP/Azure).
• Simple visualization for QA around entries/exits; containerized deploys; feature flags/presets persistence.