Staff Engineer (Big Data)

TL;DR

Staff Engineer (Big Data): Architecting and driving the technical direction of critical components for a large-scale open data platform with an accent on distributed systems and data infrastructure. Focus on building next-generation storage and query optimization systems, resolving complex performance bottlenecks, and leading open-source contributions.

Location: On-site in Kitchener

Company

hirify.global provides an advanced data observability platform used by enterprises to manage, monitor, and optimize petabyte-scale data ecosystems.

What you will do

• Drive end-to-end architecture and technical roadmaps for major platform components.
• Architect distributed systems for data storage, processing, and query optimization.
• Lead contributions to Apache projects to advance the platform and brand.
• Resolve complex performance bottlenecks and system failures at scale.
• Mentor senior engineering staff and enforce high architectural standards.
• Collaborate across bare metal, VM, and Kubernetes environments.

Requirements

• 9+ years of software development experience with 5+ years in distributed systems or big data.
• Expert-level proficiency in Java or Scala, with strong Python skills.
• Deep expertise with big data technologies like Hadoop, Spark, Trino, or Kafka.
• Advanced knowledge of Kubernetes, Linux kernel tuning, and system-level debugging.
• Must possess valid work authorization for Canada.
• Proven capability to lead high-impact architectural initiatives and mentor teams.

Nice to have

• Committer status or significant contributions to Apache projects (Spark, Kafka, Flink).
• Experience with table formats like Apache Iceberg, Delta Lake, or Hudi.
• Experience in data governance, security, or data lake architectures.

Culture & Benefits

• Opportunity to define architecture for global enterprise-scale data platforms.
• Work alongside industry experts and active Apache project committers.
• Engage in deep-tech innovation and open-source development.
• Environment focused on architectural ownership and continuous learning.