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Our client, a growing MSP is building a next-generation, cloud-native data platform from the ground up and is seeking a Senior Data Platform Engineer to play a key role in its design and development. This is a rare opportunity to work on greenfield development, helping architect and build a modern, scalable platform that transforms large-scale telemetry and operational data into actionable insights for analytics, automation, and AI-driven decision-making. Working within a collaborative engineering team, you will design secure, high-performance, multi-tenant cloud solutions while influencing technical direction, establishing engineering best practices, and delivering a platform that will support the company's future growth. If this sounds like you please apply directly or send your resume to info@stellar-recruitment.com. Responsibilities Design, build, and scale a cloud-native data platform on AWS, creating secure, resilient, and high-performing solutions capable of processing millions of telemetry events across a multi-tenant SaaS environment. Develop and optimize high-performance data pipelines, ETL/ELT processes, RESTful APIs, and backend services while designing efficient PostgreSQL database schemas and data models for structured, semi-structured, and time-series data. Build and manage cloud infrastructure using AWS, Terraform, Docker, Kubernetes, and modern CI/CD pipelines to automate deployments and support reliable, repeatable platform operations. Implement security, governance, and compliance best practices, including role-based access control (RBAC), encryption, tenant isolation, audit logging, metadata management, and data quality standards. Design and enhance platform observability by implementing monitoring, logging, distributed tracing, dashboards, alerting, and automation to improve reliability, scalability, and operational performance. Provide technical leadership through architecture reviews, code reviews, engineering standards, mentoring, and technical decision-making while driving continuous improvements across the platform. Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related discipline, combined with 6+ years of experience in Data Engineering, and Data Platform Engineering. Strong hands-on experience with AWS cloud services, including designing and operating cloud-native applications, distributed systems, and scalable production environments. Advanced proficiency in Python, SQL, and PostgreSQL, with experience building production-grade data platforms, telemetry pipelines, RESTful APIs, and backend services. Experience with modern cloud infrastructure technologies, including Docker, Kubernetes, Terraform (Infrastructure as Code), Git, and CI/CD pipelines, preferably using GitHub Actions or similar tooling. Solid understanding of data modeling, database design, distributed systems, performance optimization, and cloud architecture, with experience building highly available, scalable, and secure platforms. Experience with technologies such as Kafka, Redis, Prometheus, Grafana, OpenTelemetry, event-driven architecture, or data governance and security best practices is considered an asset, along with excellent analytical, problem-solving, and communication skills. Salary: $140,000 - $165,000 annually depending on experience Hybrid work environment, three days per week in Burnaby, BC Please note that the posted pay range for this role may vary based on seniority, qualifications, or prior experience. We are always looking for talented people to join our network, and if your desired compensation isn't reflected in this posting, please send your application for review regarding related opportunities.

What you’ll do

Design and scale a cloud-native data platform on AWS to process large-scale telemetry data in a multi-tenant environment. Develop high-performance data pipelines, backend services, and implement robust security, observability, and governance standards.

Requirements

Requires a Bachelor's degree in Computer Science or related field with over 6 years of experience in Data and Platform Engineering. Proficiency in Python, SQL, and AWS is essential, along with experience in Infrastructure as Code and containerization.

Listed skills

• Kubernetes · Preferred
• SQL · Preferred
• CI/CD · Preferred
• Redis · Preferred
• PostgreSQL · Preferred
• Docker · Preferred
• Amazon Web Services · Preferred
• Terraform · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• AWS
• Python
• SQL
• PostgreSQL
• Terraform
• Docker
• Kubernetes
• CI/CD
• Data Modeling
• ETL/ELT
• RESTful APIs
• Distributed Systems
• Kafka
• Redis
• Prometheus
• Grafana

Job areas

• Data & Analytics
• Software
• Technology
• Engineering