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Senior Data & Systems Architect (Quantitative Investment Firm)

Edge Stackers • Australia
Relocation
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Build production-grade data pipelines, AI workflows, and cloud infrastructure for a quantitative investment firm. Requires expertise in Python, SQL, and cloud systems with ownership of end-to-end solutions. Ideal for architects who thrive at the intersection of data, software, and operations.

Key Highlights
Own end-to-end data pipelines, AI workflows, and production systems
Strong Python and SQL skills required with cloud infrastructure expertise
Focus on observability, cost, latency, and incident prevention in production
Key Responsibilities
Design and build data ingestion, storage, and query systems for trading data
Develop and optimize pipelines from data ingestion to deployment and monitoring
Choose and implement cloud-based architecture with focus on robustness and cost-effectiveness
Implement infrastructure as code, CI/CD, and testing for reproducible environments
Build and operate AI/agentic workflows with measurable outputs and failure modes
Ensure observability, cost control, latency management, and incident response in production
Technical Skills Required
Python SQL Cloud Infrastructure (e.g., AWS/GCP)
Benefits & Perks
Flexible compensation based on contribution
Relocation assistance provided
Small, high-impact team with direct ownership of outcomes
Nice to Have
Experience with quantitative finance or investment systems
Knowledge of data validation, lineage, and recovery mechanisms
Background in AI/ML model deployment and monitoring

Job Description

Opportunity on the Sunshine Coast, Queensland

Edge Stackers is a quantitative investment firm built around a simple idea: good decisions come from better evidence, built into systems that work when it counts. We are a small team with high standards and room for exceptional people to shape what comes next.

We are looking for an architect-builder who can work across data, software and production systems. You can turn imperfect data into dependable systems, design the platform around it, put decision workflows and model outputs to work in production, and own the result. What you will own:

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