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Senior Backend Software Engineer – Data Platform

Kaseya Careers -
Toronto, ON

Postuler rapidement

Détails du poste

De 205 000 $ à 240 000 $ par an

Profil recherché

Expérience en développement de données
Optimisation des performances
Génie logiciel
Développement de l'automatisation des tests en assurance qualité
Databricks
Intégration des données
Azure
Rust
Go
Droit
Orchestration de conteneurs
Infrastructure as Code (IaC)
Spark
Conception de systèmes
Google Cloud Platform
Snowflake
Java
Microservices
Expérience en ingénierie du cloud
Architecture orientée événements
C++
Docker
Apache Airflow
Systèmes distribués
Scala
Terraform
RabbitMQ
Développement dorsal
Mentorat
APIs
Prometheus
Grafana
Apache
Kafka
Redshift
Logiciel-service
Intelligence artificielle
Expérience en développement logiciel ou en architecture
BigQuery
Python
Débogage
Modélisation dimensionnelle

Description complète du poste

About Kaseya

Kaseya is the leading provider of AI-powered IT management and cybersecurity software, serving Managed Service Providers (MSPs) and internal IT organizations worldwide. Our comprehensive platform helps organizations efficiently manage, secure, and automate their IT environments, driving operational efficiency and long-term business success.

Backed by Insight Partners, a leading global software investor, Kaseya has experienced sustained double-digit growth and continues to expand its global footprint. Today, Kaseya supports customers in more than 20 countries and manages over 15 million endpoints worldwide.

Founded in 2000, Kaseya has built a culture centered around innovation, accountability, and results. We are a high-growth, high-performance organization that values individuals who are driven, adaptable, and committed to delivering exceptional outcomes for our customers and teammates alike.

At Kaseya, success comes from embracing challenges, moving with urgency, and continuously raising the bar.

Senior Software Engineer – Data Platform

Location: Toronto, Canada

Why Kaseya?

Kaseya powers millions of endpoints and serves thousands of customers worldwide. We are building a new Data & AI Platform that will unify data across Kaseya products and enable new customer experiences, automation, analytics, and AI capabilities.

We are looking for strong backend software engineers who want to solve large-scale data problems.

This is a software engineering role within the Data & AI Platform organization. You will design and build distributed backend services and platform infrastructure responsible for ingesting, processing, serving, and exposing data across Kaseya products.

This is not a traditional ETL, BI, analytics engineering, or data warehousing role.

Strong candidates typically come from backend engineering, distributed systems, infrastructure, streaming, or software-oriented data platform backgrounds.

What You'll Build

You will work on greenfield platform capabilities that sit across Kaseya's product ecosystem.

You will:

Design and build backend services, APIs, and distributed platform components used by internal engineering teams and customer-facing products
Build highly available services capable of processing and serving large volumes of data
Design event-driven and asynchronous systems using technologies such as Kafka and other distributed messaging platforms
Develop services responsible for data ingestion, enrichment, routing, transformation, and delivery
Build APIs and service interfaces that expose platform capabilities to other engineering teams
Design systems that operate correctly under concurrency, partial failures, retries, duplicate events, and high load
Solve distributed-systems problems involving:
- partitioning
- ordering
- idempotency
- retries
- state management
- backpressure
- consistency
- fault tolerance
- delivery guarantees
Build reusable frameworks and platform primitives that can be adopted across multiple Kaseya products
Design service contracts, APIs, schemas, and integration patterns between independently developed systems
Improve platform performance, scalability, reliability, and operational efficiency
Build production observability using metrics, logging, tracing, dashboards, and alerting
Write automated unit, integration, and system tests
Own services throughout their lifecycle, including design, implementation, deployment, production support, incident response, and optimization
Participate in architecture reviews and technical design discussions
Collaborate closely with Product, Infrastructure, Security, AI, and other Software Engineering teams
Mentor engineers and help establish strong software engineering standards

What We're Looking For

Required

6+ years of professional software engineering experience
Significant recent hands-on experience building backend, platform, or distributed systems
Strong programming ability in one or more general-purpose languages such as:
- Java
- Go
- Python
- Scala
- Rust
- C++
Experience designing and developing production APIs, microservices, backend services, or platform services
Strong understanding of software engineering fundamentals, including:
- data structures and algorithms
- concurrency
- asynchronous programming
- API design
- testing
- debugging
- system design
Experience designing or operating distributed systems in production
Experience with event-driven architectures or distributed messaging systems such as:
- Kafka
- Kinesis
- Event Hubs
- Pub/Sub
- RabbitMQ
- similar technologies
Experience building systems that handle failures, retries, duplicate processing, ordering, and distributed state
Experience operating cloud-native production systems on AWS, Azure, or GCP
Experience owning production services, including troubleshooting, monitoring, incident response, and reliability improvements
Experience working with Docker and containerized production environments

Strongly Preferred

Deep production experience with Apache Kafka
Experience with streaming frameworks such as:
- Apache Flink
- Spark Structured Streaming
- Kafka Streams
- Apache Beam
Experience designing high-throughput or low-latency systems
Experience with CDC, event sourcing, asynchronous processing, or message-driven architectures
Experience designing partitioning and sharding strategies
Understanding of message delivery semantics such as at-most-once, at-least-once, and effectively/exactly-once processing
Experience implementing idempotent and fault-tolerant services
Experience with Kubernetes and production container orchestration
Infrastructure-as-code experience with Terraform, Pulumi, CloudFormation, or similar tooling
CI/CD and deployment automation experience
Experience with distributed caching, queues, key-value stores, or high-performance databases
Experience designing developer-facing platforms or shared infrastructure used by multiple engineering teams
Strong observability and SRE practices using technologies such as Prometheus, Grafana, Datadog, OpenTelemetry, or similar systems
Experience conducting architecture reviews or authoring technical design documents, RFCs, or ADRs

Data Platform Experience

You do not need to come from a traditional Data Engineering background.

However, you should be comfortable working with data-intensive systems.

Relevant experience may include:

Real-time data ingestion
Streaming platforms
Distributed processing
Change Data Capture
Data-serving infrastructure
Large-scale analytical systems
Data APIs
Lakehouse infrastructure
Distributed storage systems
High-volume event processing

Experience with technologies such as the following is useful, but not a substitute for strong software engineering fundamentals:

Spark
Databricks
Snowflake
Iceberg
Delta Lake
BigQuery
Redshift

Candidates whose experience is primarily focused on ETL development, BI/reporting, dimensional modeling, dashboards, or data warehouse implementation without substantial backend software engineering experience are unlikely to be a fit for this role.

Bonus

Experience building infrastructure supporting machine learning or AI systems
Experience building AI/LLM backend services
Experience with vector databases or high-scale retrieval systems
Experience with RAG infrastructure or AI data pipelines
Experience developing internal developer platforms
Experience with large multi-tenant SaaS systems
Experience mentoring engineers or leading cross-team technical initiatives

What Strong Candidates Tend to Look Like

You may have previously held titles such as:

Senior Software Engineer
Backend Engineer
Distributed Systems Engineer
Platform Engineer
Infrastructure Engineer
Streaming Platform Engineer
Data Platform Engineer
Software Engineer, Data Infrastructure

Your title matters less than what you have actually built.

We are particularly interested in engineers who can demonstrate hands-on ownership of production software systems and explain the architectural decisions, trade-offs, failures, and operational challenges behind them.

The expected base salary range for this position is CAD $205,000 to $240,000 per year. Where a candidate falls within this range depends on job-related factors such as experience, skills, and qualifications. This range reflects base salary only and does not include variable compensation or other components of the total package.

Additional Information

Kaseya provides equal employment opportunity to all employees and applicants without regard to race, religion, age, ancestry, gender, sex, sexual orientation, national origin, citizenship status, physical or mental disability, veteran status, marital status, or any other characteristic protected by applicable law.

#IND525

Additional information
Kaseya provides equal employment opportunity to all employees and applicants without regard to race, religion, age, ancestry, gender, sex, sexual orientation, national origin, citizenship status, physical or mental disability, veteran status, marital status, or any other characteristic protected by applicable law.

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