Top Tech Jobs & Startup Jobs in Toronto

The Senior Pyspark Data Engineer will manage large-scale data processing systems, conduct feasibility studies, provide user support, and develop security measures while acting as a subject matter expert in applications development.

The Senior Java Engineer will design and develop middleware services, ensure project delivery, analyze systems for performance, and contribute to code reviews while adhering to engineering standards.

The role involves leading application systems analysis and programming, managing a team, and working closely with data engineers to deliver high-quality products on the Data Technology team.

This role involves designing and developing scalable data solutions, automating tasks, and collaborating with teams to deliver business value. Responsibilities include strong database development using SQL and Python, as well as leading innovative projects and ensuring compliance.

Lead design, development, and maintenance of Java-based applications using Spring Boot and microservices. Build RESTful APIs, integrate with Oracle and MongoDB, deploy via Docker/OpenShift, and collaborate across teams. Provide technical leadership, mentor mid-level developers, drive system analysis, resolve complex issues, and ensure solutions align with architecture and compliance standards.

Provide L2/L3 technical and business support for custody, digital assets, and settlements applications. Manage incidents and major outages, partner with development and infrastructure teams to drive stability and resiliency, run ITIL processes, coordinate disaster recovery and resiliency testing, define onboarding standards, coach and train team members, and serve as SME to stakeholders while recommending system enhancements and process improvements.

As a Senior Data Engineer, you will build a data platform, create data pipelines for market and trade data, and collaborate with traders and quants to enhance analytical workflows.

Lead and manage teams to design, build, and deploy AI/ML systems with emphasis on LLMs, RAG, NLP, and MLOps. Drive technical strategy, resource and budget planning, standards, risk assessment, and cross-functional influence while ensuring compliance and supervisory accountability.

Lead enterprise Generative AI strategy and engineering: select and deploy LLMs, design RAG and agentic systems, build production GenAI services, establish governance, observability, cost controls, and reusable accelerators while managing senior engineering teams and cross‑functional stakeholders.

The role involves developing applications, conducting feasibility studies, providing user support, risk assessment, and following agile methodology. Requires Java expertise and managing projects.