Staff Software Engineer

Acceldata; Kitchener; On-site; CAD 140,000 - 200,000; Full time

Job summary

Acceldata seeks a Staff Engineer to lead architecture for the Open Data Platform (ODP) and drive the technical direction across hybrid and multi-cloud environments. You will mentor senior engineers and collaborate with Apache communities to advance large-scale data infrastructure.

You will own design decisions for scalable systems, improve performance, and guide cross-functional teams on data storage, processing, and query optimization strategies.

Qualifications

• 9+ years of hands-on software development experience.
• Expert in distributed systems and big data platforms.
• Proficient in Java or Scala with strong Python skills.
• Experience with Kubernetes, Docker, and cloud platforms.

Responsibilities

• Own end-to-end architecture of major platform components, driving scalability and reliability.
• Architect and implement next-generation distributed data storage, processing, and query optimization.
• Partner with product and leadership to define technical roadmaps and translate requirements.
• Lead contributions to Apache projects and open-source communities.
• Identify and resolve complex performance bottlenecks across distributed systems.

Skills

Distributed systems

Big data platforms

Java/Scala

Python

Kubernetes

Docker

Cloud platforms

CI/CD

Linux

Apache projects

Tools

Maven

Gradle

SBT

GitHub

Nexus

CI/CD tooling

Job description

We are seeking a Staff Engineer with at least 9 years of experience in distributed systems or data platform development. In this role, you will be a technical leader responsible for architecting and driving the technical direction of critical components within the Acceldata Open Data Platform (ODP). You will work on solving the most challenging distributed systems problems, contribute to open-source communities, and mentor senior engineers while shaping the future of large-scale data infrastructure.

You'll lead high-impact initiatives that directly influence how petabyte-scale data is managed, observed, and optimized across hybrid and cloud ecosystems. You'll collaborate with industry experts, Apache committers, and seasoned engineers who share your passion for distributed systems and open-source innovation.

Responsibilities:

• Own the end-to-end architecture of major platform components, driving design decisions that impact scalability, reliability, and performance.
• Architect and implement next-generation distributed data storage, processing, and query optimization systems.
• Partner with product, engineering leadership, and stakeholders to define technical roadmaps and translate business requirements into scalable solutions.
• Lead contributions to Apache projects and open-source communities, establishing Acceldata’s presence and technical reputation.
• Identify and resolve complex performance bottlenecks across distributed systems, optimizing for cost, latency, and throughput.
• Mentor and guide Senior Software Engineers, fostering technical excellence and a culture of continuous learning.
• Establish and enforce coding standards, perform thorough code reviews, and ensure architectural consistency across the platform.
• Evaluate and recommend emerging technologies, tools, and frameworks that align with platform goals.
• Lead root cause analysis for critical production issues and drive systemic improvements to prevent recurrence.
• Work across diverse environments: Bare Metals, VM, Kubernetes, and multi-cloud architectures.

Requirements:

• 9+ years of hands-on software development experience with at least 5 years focused on distributed systems or big data platforms.
• Expert-level proficiency in Java or Scala, with strong Python skills. Experience with systems languages is a plus.
• Deep understanding of distributed computing principles, including consensus algorithms, data partitioning, replication, fault tolerance, and consistency models.
• Extensive hands-on experience with multiple components of the big data stack (Hadoop, Spark, Hive, Trino, Kafka, Flink, NiFi or similar).
• Expert-level Linux proficiency, including kernel tuning, performance analysis, and debugging at the system level.
• Strong experience with Kubernetes, Docker, and cloud platforms (AWS, GCP, or Azure).
• Deep expertise with Maven, Gradle, or SBT; experienced in CI/CD pipelines, GitHub, and artifact management (Nexus).
• Proven ability to diagnose and resolve complex issues, including memory leaks, deadlocks, GC tuning, and distributed system failures.
• Strong understanding of architectural patterns for scalable, fault-tolerant distributed systems.
• Excellent written and verbal communication skills; ability to articulate complex technical concepts to diverse audiences, including senior leadership.
• Demonstrated ability to work effectively with cross-functional teams, external contributors, and the open-source community.

Preferred:

• History of significant contributions or committer status in Apache projects (e.g., Spark, Kafka, Hive, Iceberg, Flink, etc.).
• Experience with modern table formats (Apache Iceberg, Delta Lake, Hudi) and data lake architectures.
• Familiarity with data governance, security, lineage, and compliance frameworks.
• Experience leading large-scale data platform migrations or Hadoop distribution upgrades.
• Published technical blogs, papers, or conference presentations on distributed systems topics.
• Experience leading or maintaining open-source projects.