Exceptional written and verbal English with complete fluency.
10+ years of overall experience in software development.
5+ years of experience as a lead software developer and co-founder of a software development studio/agency/company.
5+ years of TypeScript experience.
5+ years of backend web development experience (e.g., Node.js, Go, Ruby on Rails).
5+ years of React experience.
Computer Science degree (major or minor).

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RemoteFlexible Schedule

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Remote

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Principal Software Engineer

Mastercard

Chicago, IL 60290

RemoteUrgently HiringEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Extensive experience in designing and delivering large-scale, distributed systems and platforms.
Proven ability to influence technical strategy and drive architectural decisions across multiple teams.
Strong expertise in modern software engineering practices, cloud-native architectures, and AI/data platforms.
Exceptional communication and leadership skills with a track record of mentoring and thought leadership.
Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline.
Data Architecture & Strategy
Focus on designing modern, scalable, governed data ecosystems.
Data strategy and product-aligned data architectures
Modern database technologies and migration away from legacy Oracle
Data lakehouse architectures supporting analytics and ML workloads
Feature catalog / feature engineering platforms
High-Throughput, Low-Latency, and Real-Time Systems
Critical for Mastercard's real-time decisioning and event-driven platforms.
Event streaming and high-throughput data pipelines
Low-latency data technologies (distributed caches, grid replacement)
Real-time transaction processing and sub-second decisioning
Rules engine design and modernization
Cloud Infrastructure, Platform Engineering & DevOps
Driving cloud-native engineering practices and operational excellence.
AWS infrastructure engineering and cloud-native platform patterns
DevOps and platform engineering (automation, CI/CD, observability, GitOps)
ML lifecycle engineering (model training, deployment, refresh, inference)
Deep, progressive experience in software engineering.
Proven technical leadership roles influencing architecture and design across multiple teams.
Proven track record of delivering large-scale, distributed systems and enterprise-grade platforms.