Job title: Software Engineer - Open Data Platform (ODP)

Location: Kitchener, Ontario, Canada

Experience: 3-5 years

About the Company

Acceldata builds enterprise data observability technology that helps organizations operate reliable, trusted data products across modern data environments. Its platform supports the data foundations behind AI, large language models, analytics, and DataOps, with a focus on making critical data dependable and usable. The company works across hybrid and cloud ecosystems, including bare-metal, virtualized, and Kubernetes environments. Its culture emphasizes fast execution, creativity, innovation, and meaningful engineering ownership. Teams collaborate across functions, contribute to open-source technologies, and engage with complex distributed-systems problems that matter to enterprise customers. Acceldata’s work sits at the intersection of data infrastructure, platform engineering, and operational excellence, giving engineers the opportunity to build systems that influence how large-scale data platforms are managed, observed, and optimized.

About the Role

As a Software Engineer on the Open Data Platform team, you will design, build, and scale components of a distributed data platform used across complex hybrid and cloud environments. You will contribute production-quality code in Java, Scala, or Python while working deeply with Linux, build systems, deployment platforms, and open-source technologies. The role combines software design, troubleshooting, performance optimization, and cross-functional collaboration, with challenges spanning bare metal, virtual machines, and Kubernetes. You will participate in architectural discussions, code reviews, and technical communication with senior leadership and external contributors. This is an on-site role in Kitchener with competitive compensation and direct influence over platform reliability, scalability, and developer experience.

Key Responsibilities

Design and develop Open Data Platform components that solve distributed-systems challenges while improving reliability, scalability, and operational performance across enterprise data environments. Build clean, efficient, and well-tested software in Java, Scala, or Python, ensuring maintainable systems that perform consistently under demanding production workloads. Own deployment and execution workflows across Linux, bare-metal, virtual-machine, and Kubernetes environments, reducing operational friction and improving release confidence. Collaborate with product, engineering, and open-source contributors to define features, resolve technical trade-offs, and deliver platform capabilities aligned with real-world data infrastructure needs. Diagnose complex software and platform issues through structured debugging and troubleshooting, restoring stability while identifying improvements that prevent recurring failures. Contribute to code reviews and architecture discussions, raising engineering standards and helping the team make sound technical decisions for long-lived platform components. Maintain project build and dependency workflows using Maven, Gradle, or SBT, strengthening repeatable builds, artifact management, and seamless software delivery. Communicate technical accomplishments, risks, and strategic insights clearly to senior leadership and broader engineering stakeholders, enabling informed decisions and strong execution.

Essential Skills & Technologies

Strong hands-on programming experience in Java or Scala alongside Python, with the ability to design production software using sound object-oriented, functional, and testing practices. Mandatory Linux proficiency for software development, deployment, execution, and troubleshooting across production-like infrastructure and distributed runtime environments. Practical understanding of distributed computing, thread and process management, virtualization, databases, and the engineering principles required to build dependable platform software. Experience with Kubernetes, Docker, and cloud environments, including the ability to reason about application packaging, orchestration, deployment behavior, and operational constraints. Working knowledge of Maven, Gradle, or SBT for project builds, dependency management, automation, and repeatable software delivery across engineering teams. Experience managing GitHub workflows and Nexus repositories, using source control and artifact management practices to support collaboration, traceability, and reliable releases. Strong coding, debugging, and troubleshooting capabilities, with clear English communication and the ability to collaborate effectively with internal teams and external open-source contributors.

Additional Plus

Contributions to Apache or other open-source projects demonstrate the ability to work transparently, review community code, and deliver improvements within publicly maintained software ecosystems. Experience with big data stacks or distributed data components, including application deployment, strengthens the ability to solve platform challenges at enterprise scale. Experience building in-house automation for platform management can improve operational consistency, reduce manual intervention, and accelerate the adoption of reliable infrastructure practices.

What You'll Bring

At least three years of hands-on experience developing distributed systems, data platforms, or other infrastructure software that must remain reliable under scale and operational complexity. Strong ownership of software quality, from design and implementation through testing, deployment, debugging, and performance improvement across varied infrastructure environments. A collaborative engineering mindset, with the confidence to contribute to architecture discussions, work with open-source communities, and explain technical decisions to senior stakeholders. Curiosity about evolving data infrastructure, open-source platforms, and cloud-native technologies, paired with the judgment to turn emerging ideas into stable, maintainable production systems.

Why Join Us

You will work at the foundation of modern data operations, building open platform capabilities that help enterprises trust and operate the data powering AI, analytics, LLMs, and critical business systems. The work spans distributed systems, Linux, Kubernetes, cloud environments, and open-source technologies, giving you broad technical depth and visible ownership. You will collaborate with experienced engineers and contributors who care about solving difficult infrastructure problems properly, not just shipping surface-level features. Your decisions will influence platform reliability, scalability, deployment experience, and the way data environments are managed across hybrid ecosystems. The role is designed for an engineer who wants challenging systems work, meaningful production impact, and the opportunity to see their contributions used across the wider data community. Acceldata’s fast-moving, innovation-oriented environment gives strong ideas room to become real systems, while close collaboration keeps execution grounded in customer and platform needs.