Top Python Jobs in Toronto

Manages data governance and data management practices across sourcing, integration, quality, metadata, lineage, classification, and stewardship. The role maintains data models and documentation, monitors data integrity, supports data profiling and discovery, and coordinates integrations between IT, business data owners, stewards, and subject matter experts. It also identifies process improvements and promotes standards, policies, procedures, and controls for trusted, accessible corporate data.

Designs and delivers scalable, resilient systems and APIs across eBay’s platform. Leads distributed-system architecture, API design and governance, service-contract standards, GraphQL and REST evolution, and technical strategies across teams. The role includes architecture and code reviews, mentoring, cross-functional collaboration, and proactively improving performance, reliability, observability, and maintainability.

Manages data governance and data management activities, including data sourcing, integration, quality monitoring, metadata, lineage, classification, modeling, and documentation. The role assesses data environments, improves data processes, supports data stewardship, conducts profiling and discovery, and coordinates between IT, business data owners, stewards, and subject matter experts. It requires PL/SQL proficiency and familiarity with databases, data lakes, warehouses, ETL, governance platforms, and analytics technologies.

Own end-to-end analytics pipelines for AI usage, developer experience, engineering productivity, and spend. Instrument telemetry, build governed ETL workflows, define trusted metrics, and create executive dashboards and visual narratives. Analyze results, recommend improvements to AI ROI and developer experience, and communicate methodology to senior stakeholders. Collaborate across data engineering, applied AI, and data science while using AI coding agents to build, test, and maintain production data systems.

Designs, deploys, and operates production Azure Kubernetes Service environments. Responsibilities include AKS architecture, networking, security hardening, scaling, upgrades, CI/CD, infrastructure as code, observability, vulnerability management, performance tuning, disaster recovery, incident response, and root-cause analysis. The role serves as the Kubernetes subject-matter expert and collaborates with application, security, and platform teams to maintain reliable, secure, and production-ready infrastructure.

Sets technical direction for APIs that provide governed access to legal content for AI agents. Owns API architecture, retrieval and search design, MCP integrations, evaluation frameworks, reliability, observability, security, and platform governance. Leads cross-team architecture decisions, mentors engineers, manages operational responsibilities, and establishes AI-assisted, spec-driven development practices for a multi-team internal platform.

Leads engineering activities spanning hardware, software, network infrastructure, system integration, controls, compliance, and technology roadmap development. Serves as a technology subject matter expert, defines system enhancements, recommends integrations, diagnoses root causes, assesses risk, mentors engineers, and drives operational improvements. The role requires strong backend programming, infrastructure, CI/CD, containerization, analytics, project management, communication, and experience in complex financial-services environments.

Leads engineering activities spanning hardware, software, network infrastructure, systems integration, controls, compliance, and technology roadmaps. Acts as a technology subject matter expert, defines system enhancements, recommends customizations, diagnoses root causes, assesses risk, and mentors junior staff. The role requires backend programming, databases, networking, REST APIs, CI/CD, containerization, analytics, project management, and process improvement experience in complex environments.

Own and scale the backend platform for Hapiko’s voice-activated sticker printer, including APIs, job queues, real-time device connections, cloud infrastructure, autoscaling, observability, cost instrumentation, release engineering, security, privacy, and on-call operations. The role requires production infrastructure ownership, experience scaling queue-driven or real-time systems, and strong Python and PostgreSQL skills, with Elixir experience or willingness to learn.

Assess and manage market risks across asset classes, including interest rates, credit spreads, currencies, and derivatives. Conduct stress testing, scenario analysis, risk assessments, limit reviews, and breach escalation. Prepare market risk reports and provide exposure analysis to senior management. Collaborate with trading, portfolio management, finance, and business teams on risk mitigation. Support risk governance, regulatory compliance, policy development, model changes, and process improvements.

Provides day-to-day operational support for CyberArk and privileged access management services. Manages incidents, requests, privileged accounts, service health, troubleshooting, documentation, and SLA-driven support. Collaborates with engineering, business, application, and technology teams on issue resolution, upgrades, service improvements, and projects. Maintains procedures and knowledge articles while identifying opportunities to improve operational efficiency, service quality, and user experience.

Lead the design, development, maintenance, and optimization of a scalable PnL reporting platform for trading risk operations. Manage infrastructure, environments, CI/CD, monitoring, Hadoop ecosystems, and web/API platforms. Troubleshoot bottlenecks, automate maintenance and workflows, improve developer productivity, support platform stability, and collaborate with engineering and production teams. The role also requires technical leadership, migration experience, and strong communication skills.

Provide technical support for Airbyte’s cloud and embedded integration platform. Troubleshoot APIs, connectors, data pipelines, SaaS integrations, authentication, and SDK configurations; reproduce bugs and collaborate with Engineering and Product on fixes. Support onboarding, document solutions, improve knowledge processes, and partner with Sales and Customer Success. The role requires strong API expertise, cloud and data integration knowledge, customer communication skills, and experience using AI tools to improve troubleshooting or automation.

Designs, develops, deploys, and optimizes machine learning and deep learning models for customer-facing applications. Responsibilities include experimentation, data analysis, model improvement, production deployment, scalable AI infrastructure, data and training pipelines, cloud integration, and system design. The role also involves applying current research, participating in code reviews, and collaborating with product, design, and engineering teams.

Work with sales and technical contacts to architect and demo voice AI solutions, create enablement and self-service tools, scale integrations, and productize common patterns while supporting enterprise customer deployments.

Own and evolve Clutch’s end-to-end data platform, including scalable warehouse architecture, production ELT pipelines, analytics data models, quality monitoring, observability, governance, and DevOps practices. Partner with analysts, data scientists, and business stakeholders to support decision-making and financial services initiatives. Mentor engineers, improve technical standards, and use AI to accelerate development.

Analyze financing funnels and buyer journeys, build affordability and financing-intent models, design experiments, and quantify financing’s impact on conversion, order value, and customer lifetime value. Partner with product, marketing, engineering, data engineering, and external financial-services teams to improve pre-qualification, customer decision tools, and financing performance.

Leads the design, deployment, automation, and operation of secure enterprise cloud platforms across AWS and Azure. Builds Terraform infrastructure modules, CI/CD pipelines, and cloud data lake platforms while supporting Kubernetes, GitOps, security controls, governance, monitoring, compliance, reliability, and cost optimization. Collaborates with security teams, participates in audits, and promotes platform engineering best practices across development teams.

Designs, administers, secures, and continuously improves enterprise cloud, networking, identity, Microsoft 365, and telephony platforms. Manages AWS, Azure, Microsoft 365, enterprise networks, hybrid-cloud connectivity, unified communications, IAM, security, compliance, disaster recovery, and business continuity. Automates infrastructure provisioning and operations with Terraform, PowerShell, Python, Bash, and CI/CD pipelines. Supports monitoring, troubleshooting, optimization, vendor management, and infrastructure strategy across complex business-critical environments.

Build end-to-end AI observability capabilities, including data ingestion, infrastructure, data models, and product visualizations. Develop systems that surface AI signals such as cost, token usage, errors, and anomalies. Collaborate with product and design teams to deliver customer-facing SaaS features, iterate through experimentation, and support production systems through an on-call rotation.

Own end-to-end development of AI observability capabilities, including data ingestion, infrastructure, data modeling, and product visualizations. Build systems surfacing AI cost, token usage, errors, and anomalies while collaborating with product and design teams. Ship customer-facing SaaS features, teach AI debugging best practices, iterate through experimentation, participate in on-call rotation, and potentially develop LLM or agent-powered production features.

Build and optimize distributed Lance dataset operations, high-performance indices, table formats, and data encodings in Rust. Develop integrations with Spark, Hive Metastore, Presto, Trino, Ray, and other data infrastructure systems. Improve internal data processing infrastructure, contribute to open-source communities, and promote Lance through technical conferences. The role requires deep distributed systems expertise and extensive experience with high-performance databases, big data, or AI training systems.

Conduct product security reviews, threat modeling, penetration testing, manual code reviews, and architectural assessments. Identify vulnerabilities, lead security incidents, guide engineering teams, build security automation, assess AI and LLM security, mentor junior engineers, and communicate findings through documentation, research, presentations, and publications.

Administers and optimizes enterprise Microsoft SQL Server and MongoDB environments. Responsibilities include monitoring, patching, performance tuning, capacity management, incident and change management, root cause analysis, high availability and disaster recovery, backup and recovery, automation scripting, cloud support, security compliance, and technical documentation. The role also troubleshoots cross-layer infrastructure issues, supports deployments, collaborates with engineering teams, and mentors junior staff.

Design, develop, refactor, and migrate legacy ASP.NET and backend applications using Python and C#. Build microservices, containerize with Docker/Kubernetes (EKS), deploy to AWS, ensure application security, and optimize SQL database performance while collaborating with cross-functional teams.