Senior Data Engineer (Streaming + AI Systems)

Calliere • Toronto, ON

8d

About The Position

We’re partnered with a capital-backed operator in the industrial / infrastructure space that’s investing heavily in building a modern data platform from the ground up. They’re hiring a Senior Data Engineer to lead the design and evolution of real-time data systems and scalable architecture supporting both operational intelligence and predictive modelling. This is a high-ownership role at the intersection of data engineering, applied statistics, and production AI. You’ll operate as a senior individual contributor with end-to-end responsibility across pipelines, platform design, and ML enablement. This role offers true ownership of the data platform, including architecture, pipelines, and production ML systems, with a direct impact on operational performance and financial strategy. You will have senior-level autonomy with influence over technical direction and tooling choices in a lean, execution-focused team where senior engineers build and ship complete systems. This position offers long-term stability paired with a builder environment and modern stack.

Requirements

• Proven experience building and scaling data platforms in production environments.
• Deep expertise in streaming systems and distributed data processing.
• Strong system design skills with the ability to operate at both architecture and implementation levels.
• Experience owning ML/data pipelines end-to-end, including production deployment.
• Solid grounding in statistical modelling and real-world applications.
• A bias toward ownership, pragmatism, and building systems that actually get used.
• AWS (Glue, Lambda, ECS, S3, and related services)
• Apache Spark + lakehouse frameworks (Delta or equivalent)
• Kafka / streaming architectures
• Terraform (Infrastructure as Code)

Responsibilities

• Architect and operate real-time and batch data pipelines (Kafka, Spark, AWS ecosystem).
• Lead the evolution of a scalable lakehouse architecture for analytics and ML workloads.
• Design and productionize end-to-end ML pipelines, including feature engineering and real-time inference.
• Apply statistical methods (time-series, regression, anomaly detection) to high-impact business problems.
• Partner with stakeholders across operations, finance, and product to translate complex requirements into robust systems.
• Own infrastructure design using IaC (Terraform or equivalent) to ensure reproducibility and scale.
• Drive performance, reliability, and observability across data systems.
• Evaluate and introduce new tools and patterns across data engineering and applied AI.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed