Senior ​/ Staff Software Engineer – Core Data Infrastructure

The Company

We are representing a well-capitalized, fast-growing B2B technology company that builds high-volume data aggregation platforms. Their infrastructure ingests massive streams of sensor and mobility data from hundreds of fragmented third-party sources, unifying it into a single, reliable API. Some of the largest enterprises in the logistics, transportation, and risk-management sectors rely on this backbone for real-time analytics. The engineering team operates out of a Toronto hub, tackling petabyte-scale challenges with the agility of an early-stage startup and the rigor of a mature tech organization.

This is a foundational backend and systems engineering position, not a traditional data engineering or pipeline-maintenance role. You will be architecting the core distributed systems that ingest, process, and store terabytes of time-series data daily. You will own the full lifecycle of the platform’s data flow, building the highly available, resilient primitives that internal product teams and external enterprise clients build upon.

• Design, build, and optimize high-throughput data processing systems (both real-time streaming and batch).
• Engineer robust storage solutions capable of handling rapidly expanding volumes of time-series and spatial data without compromising on query performance.
• Drive architectural decisions to ensure the infrastructure remains fault-tolerant and ahead of the company s aggressive scaling trajectory.
• Develop intelligent, automated tooling that improves data quality, lineage tracking, and system reliability.
• Collaborate closely with internal stakeholders to define technical abstractions that can be reused across different product lines.
• Write scalable, production-ready code, primarily utilizing Java and Python.

• Scale
  
  Experience:
  
  A proven track record of designing and maintaining distributed backend systems or data platforms that process data at the terabyte or petabyte scale.
• Technical Foundation:
  Deep expertise in computer science fundamentals, system architecture, and anticipating failure modes in complex networks.
• Language Proficiency:
  Advanced proficiency in a JVM language (Java, Scala, Kotlin) and a willingness to work across different stacks as needed.
• Data Ecosystems:
  Hands-on experience with modern large-scale processing frameworks (e.g., event streaming, distributed computation, and advanced data warehousing/lakehouse concepts).
• Autonomy:
  High comfort level navigating ambiguity. You know how to scope complex problems, make definitive architectural calls, and drive projects to completion independently.

• Active contributions to open-source software, particularly in the distributed systems or data infrastructure space.
• Familiarity with modern orchestration engines, lakehouse architectures, or spatio-temporal data models.

Work Environment

• High Autonomy:
  Engineers own their domains end-to-end and have a direct voice in product direction.
• Proximity to the User: A culture of speaking directly with customers to understand their friction points before writing a single line of code.