Principal Software Engineer, Distributed Systems

Alteryx is leading the transformation in data, automation, and AI to help organizations make better business decisions. They are looking for a Principal Engineer to drive and own the software architecture for their core platform, focusing on large-scale, distributed systems and collaborating with various teams. The role involves defining architectural standards, mentoring engineers, and ensuring the architecture is operable and maintainable in production.

Responsibilities:

• Define, evolve, and own the architectural vision and roadmaps for the major platform domains (e.g. orchestration, job execution, data pipelines, sidecar services)
• Perform architecture reviews, assess proposals from teams, and vet designs for adherence to standards, scalability, performance, reliability, and security
• Lead or contribute hands-on to critical subsystems (e.g. orchestrator, scheduling, service mesh, job pipelines, stateful services)
• Drive and enforce cross-team architectural patterns
• Provide thought leadership: prototype proofs-of-concept, evaluate new tools/technologies, bring innovation into the platform
• Mentor and coach architects, senior engineers, and guide teams through architectural change
• Collaborate with infrastructure, operations, SRE, security, and DevOps to ensure the architecture is operable, observable, and maintainable in production
• Help define and lead architecture governance (e.g. architecture review board, reference architectures, standards, guidelines)
• Participate in tech strategy, roadmap planning with product & engineering leadership
• Diagnose and resolve technical debt or architectural “smells” across the codebase, enforcing consistency

Requirements:

• Experience: ~10+ (or more) years of software engineering experience, with at least 3–5 years in senior architect or principal-level roles (or equivalent)
• Proven track record of designing and operating large-scale, distributed systems in a production environment
• Deep hands-on experience with orchestration, scheduler systems, job pipelines, or workflow engines
• Strong proficiency in one or more of: Java / JVM ecosystem, Python, Node.js, or equivalent high-level backend languages
• Experience with message/event systems (e.g. Kafka or similar), queueing, streaming architectures
• Familiarity with in-memory data stores and caching (e.g. Redis or equivalents)
• Strong knowledge of containerization, Kubernetes, sidecar patterns, service meshes, proxies, etc
• Understanding or experience in split-plane architectures (control plane / data plane separation) is highly desirable
• Strong skills in API design, data modeling, integration patterns, error handling, consistency
• Experience with observability (metrics, tracing, logging) and designing systems for operability and failure modes
• Ability to conduct performance analysis, capacity planning, scaling, fault tolerance strategies
• Excellent communication skills—able to articulate tradeoffs, convince stakeholders, write design docs, lead design reviews
• Ability to function autonomously, make decisions in ambiguity, drive consensus across teams, and adopt/evict technologies as needed
• Strong judgment about when to optimize vs. when to simplify
• Familiarity with high-scale cloud deployments (e.g. AWS, Azure, GCP) and infrastructure-as-code is a plus