Senior Backend Software Engineer – Data Platform

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.

Location: Toronto Canada

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.

You will work on greenfield platform capabilities that sit across Kaseyas 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

• 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

• 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

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.

• 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

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 $205000 to $240000 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.

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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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.