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Added 2 mins ago
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Digivance Solutions

Software Engineer

Canada

Job type: Full-time
Experience: ● 7+ years of professional software engineering experience.
Posting language: English
Posted: Sep 30, 2026

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Original job description

Key Responsibilities

Design, build, and maintain highly scalable distributed systems and backend services.

Develop and improve systems responsible for syncing large volumes of customer data.

Optimize data-processing performance, reliability, throughput, and latency.

Design systems that support batch and real-time data synchronization.

Build and scale event collection, streaming, and messaging services.

Identify and resolve bottlenecks as systems grow by multiple orders of magnitude.

Contribute to multi-cloud and multi-region backend infrastructure.

Support systems that serve a global customer base and meet data-residency requirements.

Work closely with customers and internal engineering teams to solve challenging scaling problems.

Own projects end-to-end, from system design and technical planning through implementation and delivery.

Make sound technical decisions in an environment involving complex and ambiguous engineering challenges.

Required Qualifications

7+ years of professional software engineering experience.

Strong background in backend engineering and distributed systems.

Excellent understanding of system design fundamentals and large-scale distributed architectures.

Experience building complex backend systems from scratch rather than only integrating pre-built components.

Experience designing or developing event-collection or data-streaming systems used in business-critical environments.

Hands-on experience with technologies such as:

Message queues and event-driven systems.

Apache Kafka or similar streaming platforms.

SQL and other database technologies.

Kubernetes.

Docker.

Proven experience owning systems that have undergone significant growth and scaling them successfully.

Strong programming and software architecture skills.

Excellent communication and collaboration abilities.

Ability to learn quickly, work independently, and take ownership of ambiguous problems.

Demonstrated career progression and increasing levels of responsibility.

Preferred Qualifications

Experience building data-syncing engines that process terabytes of data per day.

Experience with real-time data systems, webhooks, queues, or streaming sources.

Experience working close to the infrastructure layer.

Strong understanding of how technologies such as Kafka, Spark, or Flink work internally.

Experience with multi-region and multi-cloud architectures.

Experience working at a high-growth technology company or startup.

Experience building systems during periods of rapid company and product growth.

Background in high-talent-density engineering environments.

Degree in Computer Science or a related field from a strong technical program.

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More about this job

Responsibilities

Design, build, and scale distributed backend systems for batch and real-time data synchronization, event collection, streaming, and messaging. Own projects from technical planning through delivery, optimize system performance and reliability, and collaborate with customers and engineering teams on complex scaling challenges.

Requirements

Requires at least seven years of software engineering experience, strong backend and distributed-systems expertise, and experience building and scaling complex systems, including event-collection or streaming platforms. Candidates should have hands-on experience with message queues, Kafka or similar platforms, SQL, Kubernetes, and Docker, along with strong architecture, communication, and ownership skills.

Skills

Backend Engineering
Distributed Systems
System Design
Data Synchronization
Data Processing
Event-Driven Systems
Apache Kafka
SQL
Kubernetes
Docker
Streaming Systems
Multi-Cloud Architecture
Multi-Region Architecture
Software Architecture
Communication
Project Ownership

Visa sponsorship

Not detected in the job text

Keywords

Backend Services
Distributed Systems
System Design
Data Synchronization
Batch Processing
Real-Time Data
Data Processing
Event Collection
Event-Driven Systems
Message Queues
Apache Kafka
Streaming Platforms
SQL
Databases
Kubernetes
Docker
Multi-Cloud
Multi-Region Architecture
Data Residency
Scalability
Throughput
Latency
Reliability
Apache Spark
Apache Flink
Webhooks
Infrastructure
Software Architecture
Customer Collaboration
Technical Planning

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