Software Engineer, Data Acquisition

About the role

The Opportunity

You'll own the systems that feed Nascent's trading and research operations with the data they need to compete — building and operating the web scraping and data acquisition infrastructure that runs 24/7 across a heterogeneous fleet of machines, providers, and operating systems. This is a roughly 50/50 split between software engineering and operations: half your time you're writing production code (primarily Rust) to build new scrapers, defeat anti-bot countermeasures, and architect resilient pipelines; the other half you're deep in logs, monitoring dashboards, and fleet health — diagnosing failures, tuning proxies, and keeping a distributed system humming across mixed infrastructure.

You'll work closely with analysts and researchers who depend on the data you deliver. The problems are genuinely interesting: every major website is actively trying to stop you, infrastructure spans multiple cloud providers and bare metal, and the surface area of what breaks is enormous. The team has a growing analyst presence in Montreal and in-person collaboration matters so this is an onsite role in our Montreal office.

Responsibilities

- Build and maintain production-grade web scraping systems — primarily in Rust — designing scrapers that are resilient to site changes, rate limiting, CAPTCHAs, and evolving anti-bot countermeasures.

- Operate and monitor a heterogeneous distributed infrastructure spanning multiple cloud providers, bare metal, and mixed operating systems — you own uptime, not just deployments.

- Diagnose production issues from raw logs and telemetry, building observability into every system you ship so problems surface before they cascade.

- Design and implement proxy management, rotation strategies, and network-layer evasion techniques to maintain reliable data acquisition at scale.

- Develop tooling for fleet health monitoring, automated alerting, and self-healing infrastructure across a diverse set of machines and hosting environments.

- Collaborate with analysts and researchers to understand data requirements, prioritize new source integrations, and ensure data quality and freshness meet trading-grade standards.

- Reverse-engineer web applications and APIs — inspecting network traffic, deobfuscating JavaScript, and adapting to adversarial changes in target sites.

- Continuously improve system reliability, throughput, and maintainability — refactoring scraping pipelines, optimizing connection handling, and reducing operational toil through automation.

- Deploy and maintain agentic workflows for data source discovery, onboarding, and troubleshooting — using LLM-based agents to automate the identification of new sources, accelerate integration, and surface and resolve failures in existing pipelines.

About you

- You are a builder who also runs what you build — you don't consider a project done when the PR merges; you consider it done when it's been stable in production for weeks.