Top Python Jobs in Toronto

Lead strategy and analytics initiatives that drive business growth, profitability, credit performance, and customer outcomes. Manage and develop analysts, build product, marketing, and credit strategies, conduct quantitative analysis and modeling, test hypotheses, and deliver recommendations to senior leaders. Partner cross-functionally with data science, engineering, process management, and marketing teams to execute strategies from concept through market delivery.

Develop requirements, designs, prototypes, and verification procedures for hardware-in-the-loop simulation test equipment. Design electronic circuits, test stations, and control software; integrate, commission, troubleshoot, and validate systems. Collaborate with multidisciplinary engineering teams, coordinate manufacturing, train users, manage equipment reliability, and ensure regulatory, safety, cost, and customer requirements are met.

Participate in an 18-month software engineering launch program, developing, testing, deploying, debugging, and securing scalable software features. Collaborate with experienced engineers, contribute to code reviews, use version control and development tools, and build solutions supporting Mastercard’s global technology platforms. The program includes structured onboarding, mentorship, learning, and hands-on project experience.

Analyze Canadian structured finance transactions, including collateral, deal structures, legal documentation, financial models, and cash-flow engines. Support rating committee presentations, reports, press releases, research, and credit recommendations. Build relationships with clients and external stakeholders while developing expertise in structured finance methodologies for ABS and ABCP transactions.

Build and scale frontend applications, backend services, APIs, integrations, and production systems. Own projects from technical design through rollout and maintenance, improve reliability, performance, scalability, and observability, and collaborate cross-functionally with Product and Design. Mentor engineers, contribute to architecture and engineering standards, resolve ambiguous technical problems, and use AI-assisted tools to accelerate development while maintaining sound engineering judgment.

Develop and administer Tableau Server, build optimized data sources and dashboards, write and tune SQL, and perform exploratory data analysis. Partner with business, product, and analytics teams to deliver scalable reporting solutions. Establish visualization standards, document analytical processes, and evaluate AI/NLP tools such as Amazon Q to improve self-service analytics and natural-language querying.

Own production database troubleshooting, performance analysis, incident root-cause analysis, and reliability improvements across large-scale PostgreSQL and MariaDB fleets. Develop observability and automation, influence multi-tenant cloud infrastructure decisions, support distributed web applications, and mentor engineers. The role requires database performance tuning, Unix administration, distributed systems expertise, stress testing, and experience with SaaS, PaaS, or cloud infrastructure products.

Owns production database troubleshooting, performance analysis, incident root-cause analysis, observability, and automation across large-scale multi-tenant PostgreSQL and MariaDB environments. The role supports distributed web applications on Unix and cloud infrastructure, influences platform decisions, develops mission-critical software, and mentors engineers. It requires database performance tuning, stress testing, distributed systems expertise, scripting, and familiarity with DevOps tools such as Kubernetes and CI/CD pipelines.

Design, build, deploy, and operate production optimization applications using advanced algorithms, machine learning, APIs, data pipelines, concurrency, and automated evaluation. Specify and review AI coding-agent work, own system quality and reliability, monitor production services, respond to issues, and collaborate with customers and cross-functional teams to translate business requirements into scalable solutions.

Engineering internship opportunities span hardware and chip design, testing and validation, systems performance, AI and machine learning, software and tools, technical enablement, and technical product programs. Interns may build, test, debug, model, analyze, or improve technical systems using programming, hardware, simulation, data, and engineering tools. Candidates must be enrolled in a relevant technical degree program and return to their studies after the internship.

Arm’s Graduate Engineering Pathways Program offers early-career opportunities across hardware and chip design, testing and validation, systems performance, AI/ML, software tools, technical enablement, and technical product programs. Graduates work on real products, solve technical challenges, learn new technologies, and collaborate with experienced teams. Candidates must be pursuing a relevant technical or quantitative university degree and demonstrate hands-on technical problem-solving through coursework, research, internships, projects, or open-source work.

Build Python-based frameworks to validate, reconcile, cleanse, and transform large datasets. Use Pandas and NumPy to identify data quality issues, discrepancies, duplicates, and anomalies. Automate validation workflows, investigate root causes, produce data quality reports, optimize processing, and collaborate with business, analytics, and engineering teams on data migration, onboarding, and integration initiatives.

Develop advanced statistical models and custom analyses to address client business challenges. Use R, Tableau, SAS, Visual Basic, Excel, and other analytic tools to guide decisions, create deliverables, and implement solutions. Communicate findings through presentations, manage client relationships, provide project updates, and mentor Associates while contributing to consulting engagements.

Monitors and investigates security alerts across SIEM, SOAR, EDR/XDR, firewall, and threat-intelligence platforms. Performs incident triage, analysis, response, escalation, malware and vulnerability management, and security-system troubleshooting. Supports tuning and process optimization, follows ITIL practices, documents procedures, and maintains customer security records. The role requires 24x7 availability, 12-hour shifts, ongoing threat awareness, and eligibility for a Government of Canada Level 2 Secret clearance.

Build and improve test infrastructure, automation frameworks, CI/CD pipelines, and end-to-end testing strategies. Lead quality initiatives, develop AI-augmented testing solutions, monitor test environments, support incident resolution, and use quality and performance metrics to improve software reliability. Collaborate with Infrastructure, SRE, engineering leaders, and product teams in an agile environment to expand test coverage and enable safe, efficient delivery.

Develops, validates, deploys, and supports machine learning, predictive maintenance, computer vision, anomaly detection, and predictive quality solutions for manufacturing. Builds data pipelines, analyzes production data, integrates AI with equipment, monitors models, and creates performance dashboards. Collaborates with manufacturing, controls, quality, maintenance, IT, and operations teams to improve quality, reliability, efficiency, FTQ, scrap, and OEE while supporting Industry 4.0 initiatives and equipment validation.

The role involves helping modernize industries through IoT solutions, engaging with clients, managing implementations, and driving tech adoption. Significant pre-sales experience is required, coupled with a strong technical background in hardware and cloud applications.

Design and maintain ETL pipelines and Databricks Gold-layer tables; develop semantic layers, data dictionaries, and documentation for AI-driven BI; build dashboards and analyses to surface marketing and sales KPIs; perform ad-hoc deep dives; translate stakeholder requirements into scalable, analytics-ready data models; enable self-serve reporting and agentic AI workflows.

Owns end-to-end reconciliation and financial reporting across card networks, banks, processors, and internal ledger data. Designs SQL-based reporting, dashboards, exception queues, metrics, controls, and automated solutions; investigates discrepancies, improves data pipelines, supports month-end close and audits, and partners with Finance, Accounting, Treasury, Tax, Compliance, Engineering, and Product. Mentors analysts and drives process improvements, automation, and responsible AI adoption.

Own end-to-end reconciliation and reporting for card networks, banks, processors, and internal ledger data. Build SQL-based reporting, dashboards, exception queues, metrics, controls, and automated solutions; investigate discrepancies, improve data quality, support month-end close and audits, and partner with Engineering, Product, Accounting, Treasury, Tax, and Compliance. The role also defines requirements and test plans, maintains data pipelines, mentors analysts, and drives automation across payment settlement and money-movement processes.

Lead reliability engineering for Braze’s NGINX ingress fleets, Kubernetes infrastructure, Ruby on Rails monolith, and Go API services. Design scalable, highly available systems; develop automated scaling routines; define SLIs, SLOs, and error budgets; conduct capacity planning; and participate in PagerDuty on-call rotations. Drive incident response, root-cause analysis, blameless retrospectives, runbook improvements, and resilient architecture decisions with product engineering teams.

Conducts advanced application security research across GitLab’s DevSecOps and AI-powered platforms. Responsibilities include discovering and exploiting systemic vulnerabilities, penetration testing, developing proof-of-concept exploits, researching AI and agentic security threats, building automated research tooling, coordinating remediation, mentoring security professionals, and communicating findings to engineering and security communities.

Conduct advanced application security research across GitLab’s DevSecOps and AI-powered platforms. Identify and exploit novel, systemic, and chained vulnerabilities; develop proof-of-concept exploits, testing methodologies, and research automation; assess AI attack vectors and open-source dependencies; drive remediation and security improvements; advise engineering teams, contribute to roadmaps, mentor researchers, and share findings with the security community.

Lead hardware and embedded security across Motive devices, including secure boot, firmware, FOTA, manufacturing, threat modeling, architecture reviews, and lifecycle risk management. Partner with hardware and engineering teams to define security requirements, validate controls, remediate findings, and build secure-by-default components. Address hardware, IoT, cloud, runtime, supply chain, and application security across device lifecycles.

The engineer will verify PCIe and CXL subsystems, collaborate on testplans, develop UVM testbenches, and improve verification methodologies.