Senior Staff Software Engineer, Data Platform & Distributed Systems
- Canada
- onsite
- Full time
- Staff
Posted
Free to apply. You’ll finish on the employer’s own site.
- Kafka
- Spark
- ETL
- Prototyping
- AWS
- Azure
+6 more
- Google Cloud
- Java
- Python
- Scala
- Rust
- Snowflake
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 was built by builders - and we're still building. We look for people who create rather than wait, who see a hard problem and lean in, and who treat challenges as raw material. At Kaseya, everyone plays a role in shaping the future of IT: whether you're in engineering, product, sales, marketing, customer support, or operations, your work helps protect, defend, and optimize IT environments across the globe.
We're building teams that grow, perform, and make an impact. If you're driven by the itch to make things better - a product, a process, a career - you'll fit right in.
At Kaseya, we don't just raise the bar. We build it.
Senior Staff Software Engineer, Data Platform & Distributed Systems
Why Kaseya?
Join a fast-growing company that’s transforming the IT industry. At Kaseya, you’ll have the opportunity to work with cutting-edge technology, collaborate with a dynamic team, and develop your career in a high-impact role.
Join the Kaseya growth rocket ship and see how we are #ChangingLives!
Job Summary
We’re hiring a Senior Staff Software Engineer to lead the architecture and evolution of Kaseya’s data platform, supporting real-time processing, analytics, and AI-powered product capabilities. This is a hands-on technical leadership role focused on distributed systems, event streaming, data infrastructure, and building reliable services that operate at scale. You will work across Data Engineering, Platform, Product, and AI/ML teams to define technical direction, lead complex engineering initiatives, and build reusable platform capabilities that support multiple products.
Roles & Responsibilities
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Define and drive architecture for large-scale data platforms, including ingestion, event streaming, distributed processing, storage, and data-serving services
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Lead complex technical initiatives across multiple engineering teams, establishing reusable platform components and reducing reliance on individual data pipelines
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Design and improve event-driven systems using technologies such as Kafka, Flink, Spark, or similar distributed processing frameworks
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Guide the development of reliable data ingestion and change data capture (CDC) systems, including schema evolution, ordering, replay, and failure recovery
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Drive technical decisions around data storage, lakehouse architectures, analytical databases, and data access patterns based on performance, scalability, and cost
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Remain hands-on through architecture reviews, technical prototyping, critical implementation, production debugging, and performance optimization
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Improve platform reliability, observability, data quality, and operational readiness across real-time and analytical workloads
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Mentor Senior and Staff Engineers, establish engineering standards, and partner with technical leadership on platform modernization and long-term architecture decisions
Required Qualifications
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10+ years of software engineering experience building production backend systems, distributed systems, or large-scale data platforms
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Experience leading architecture and technical delivery of data platform initiatives spanning multiple engineering teams or services
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Experience designing and operating production event-streaming or distributed processing systems using Kafka, Flink, Spark Structured Streaming, or similar technologies
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Experience designing production data ingestion, CDC, or distributed processing systems, including handling schema evolution, retries, ordering, replay, and failure recovery
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Experience developing and operating cloud-based data platforms on AWS, Azure, or GCP using Java, Go, Python, Scala, Rust, or similar programming languages
Preferred Qualifications
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Experience with Apache Kafka, Confluent, Apache Flink, Kafka Streams, or other stateful stream-processing technologies
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Experience with CDC technologies such as Debezium, Kafka Connect, or database replication frameworks
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Experience with lakehouse architectures and technologies such as Apache Iceberg, Delta Lake, Hudi, or Amazon S3
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Experience with analytical databases and query engines such as ClickHouse, Snowflake, BigQuery, Redshift, Pinot, or Druid
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Experience with data governance, schema registries, data contracts, lineage, metadata management, or data quality frameworks
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Experience building multi-tenant or multi-region data platforms using Kubernetes, Terraform, GitOps, or similar cloud-native technologies
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Experience supporting production AI/ML platforms, feature engineering, RAG, vector search, or real-time inference workloads
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
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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