Intermediate Software Engineer

DataStealth•Mississauga, ON

29d•Hybrid

About The Position

DataStealth is a single, unified data security platform (DSP) that discovers, classifies, and protects sensitive data across your entire environment, from on-premise to legacy cloud to cloud; wherever your data lives or flows, we protect it. We do this without requiring complex integrations or changes to your existing applications, ensuring security that enables, rather than hinders, your business. By seamlessly applying data protection strategies, such as tokenization, we ensure that even if your perimeter is breached, your data remains unusable if it falls into the wrong hands. Recognized for the fifth consecutive year as a Great Place to Work, we are one of the world’s leading and fastest growing cybersecurity software companies. Our team is the best in the business. Our patented technology provides our large enterprise customers with the ability to solve complex data security problems with a paradigm shifting technology that can actually solve problems. You’re a technically strong, systems-minded developer who takes end-to-end ownership—designing, building, and operating production services in a fast-moving scale-up environment. With strong Java fundamentals and hands-on Linux experience, you’re comfortable troubleshooting complex distributed systems issues and improving performance, reliability, and maintainability through thoughtful architecture and clean refactoring. You collaborate well across Engineering, Security, and customer-facing teams, raise the bar through mentorship and documentation, and use AI-assisted development tools as disciplined accelerators (not shortcuts) while maintaining rigorous review, testing, and production-quality standards. We are building the next generation of our platform and expanding our engineering team with polyglot developers who think in systems, not just features. You will work across our stack—designing, building, and operating high-scale distributed services that protect some of the world’s most sensitive data. This is hands-on, high-impact work where your code ships to production and directly safeguards enterprises globally. Based in Mississauga with a hybrid schedule (4 days in-office per week), you will join a collaborative, fast-moving team where engineering ownership is real: you design it, you build it, you run it.

Requirements

3+ years of professional software development experience, ideally including work on security, infrastructure, or data-intensive products
Track record of shipping production services and contributing to on-call or incident response rotations
Experience with configuration-as-code (we use Groovy) and infrastructure-as-code tooling
Familiarity with observability practices (structured logging, distributed tracing, metrics)
Proficiency in at least two of the following: Java (Must Have) , TypeScript/Node.js, Golang, Rust—with demonstrated willingness and ability to learn the others
Experience designing and developing distributed systems, microservices, or platform-level software
Solid understanding of cloud platforms (AWS, Azure, or GCP) including core services (compute, storage, networking, IAM)
Hands-on experience with Linux systems, shell scripting, and system-level debugging
Strong grasp of networking fundamentals (HTTP/S, TLS, SSH, DNS, TCP/IP) and how they apply to distributed systems
Working knowledge of CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes)
Experience with agentic AI development tools (Copilot, Cursor, Claude Code, or similar) as part of a deliberate, quality-driven engineering workflow—not as a substitute for understanding
Comfort working in a hybrid environment (Mississauga office, 4 days/week)

Nice To Haves

Experience with data security, encryption/cryptography, tokenization, or privacy-enhancing technologies
Applying AI technologies and models to security domain problems
Contributions to open-source projects in infrastructure, security, or developer tooling
Experience with event-driven architectures (Kafka, RabbitMQ, NATS)
Familiarity with database systems across paradigms (PostgreSQL, Redis, Elasticsearch, DynamoDB)
Direct experience with performance analysis and profiling across polyglot systems (Java, Node.js, Go, Rust), utilizing platform-specific tools like VisualVM/JProfiler (for Java), pprof (for Go), or Chrome DevTools/V8 Profiler (for Node.js) to diagnose and resolve issues such as memory leaks, thread contention, and critical path latency in high-throughput services.

Responsibilities

Design, develop, test, and operate cloud-native microservices and platform components that form the backbone of the DataStealth DSP
Build and scale distributed systems that handle high-throughput data discovery, classification, and protection across heterogeneous environments (cloud, hybrid, on-premise, SaaS)
Architect for resilience, observability, and performance—designing services that degrade gracefully, emit meaningful telemetry, and meet strict latency requirements
Work across the stack using the right language for the job: Java, TypeScript/Node.js, Golang, and Rust
Contribute to security products that implement tokenization, encryption, masking, and key management at enterprise scale
Apply secure coding practices, threat modeling, and DevSecOps principles as first-class engineering concerns—not afterthoughts
Collaborate with security architects to ensure platform changes maintain compliance with PCI-DSS, SOC 2, and other regulatory frameworks
Deploy and operate services across AWS, Azure, and GCP using infrastructure-as-code (Terraform, Pulumi, or CloudFormation)
Design and manage CI/CD pipelines, container orchestration (Kubernetes/Docker), and observability stacks (Prometheus, Grafana, OpenTelemetry, ELK)
Optimize cloud cost, performance, and reliability through data-driven capacity planning and SRE practices
Practice agentic software engineering: use AI development tools (e.g., GitHub Copilot, Claude Code, Open Source AI coding tools) as disciplined engineering partners—directing agents to plan, write, and test code while maintaining full engineering ownership and judgment
Distinguish between rapid AI-assisted prototyping and production-grade agentic workflows; apply rigorous review, testing, and validation to all AI-generated code before it reaches production
Contribute to the team’s AI-augmented engineering practices: prompt engineering, context engineering, automated code review with AI, and AI-assisted testing strategies
Participate in architecture discussions, design reviews, and technical decision-making across squads
Mentor intermediate and junior developers, fostering a culture of continuous learning and engineering excellence
Maintain and improve technical documentation, runbooks, and onboarding materials
Work cross-functionally with Product, Security, and Customer Success to translate complex requirements into well-scoped engineering plans