Top Python Jobs in Toronto

Lead a team to implement and monitor End-to-End Risk & Control Self-Assessments (E2E RCSA), manage people and process improvements, support regulatory compliance, handle governance projects, liaise with control partners, and provide executive reporting and data insights to maintain risk and control frameworks across TDS businesses.

Lead and operate TD Securities' data platform, providing hands-on technical guidance to solution engineers. Design, implement and monitor cloud-native infrastructure, ensure platform stability, optimize costs, drive CI/CD and observability, liaise with stakeholders, and lead complex projects delivering data ingestion-to-consumption capabilities on Azure/Databricks/Kubernetes environments.

Develop analytics solutions and dashboards using Python in AWS, apply accounting knowledge to interpret financial results, analyze complex data to uncover trends, present insights to decision makers, recommend process and data-quality improvements, and support continuous improvement of reporting and data tools.

As a Data Engineer, you will design and implement data processes, governance, and optimize data infrastructure, facilitating data-driven decisions at Gore Mutual.

Design, implement, and integrate scalable data pipelines and analytics engines for compliance and surveillance. Integrate upstream bank systems with core surveillance platforms, work with big data frameworks, cloud data lakes, and messaging systems to support AML, trade and payments surveillance.

Design and perform advanced statistical analyses and predictive models (logistic regression, decision trees, random forest, neural nets) using SAS/SQL/Python. Manage fraud rules, implement and optimize detection/prevention strategies, maintain data pipelines, and collaborate with stakeholders to deploy fraud mitigation solutions and reduce losses while improving customer experience.

Lead and grow a distributed engineering team building Sangomas UCaaS platform. Drive architecture, scalability, reliability, CI/CD, observability, incident response, and cross-functional delivery for voice, messaging, provisioning, integrations and admin services.

Lead design and hands-on delivery of full-stack prototypes and production solutions. Build front-end, back-end, cloud and data components; enforce secure, maintainable architectures; run code reviews, CI/CD, testing and monitoring; translate technical choices to stakeholders and support agile delivery with cross-functional teams.

Lead design, development, testing, and implementation of finance reporting, forecasting and analytics solutions. Build and support cross-platform data pipelines and integrations using Azure, Databricks, ADF, Python and RDBMS; liaise with finance stakeholders, vendors, and regulators; provide advisory and product-ownership responsibilities for finance modernization.

Support daily trade lifecycle activities for public markets including trade capture, confirmation, settlement, exception resolution, reconciliations, and process documentation. Troubleshoot system/data issues, act as an expert user of OMS/STP systems, contribute to projects, testing and automation, and provide client and vendor support to maintain operational controls and improve efficiency.

Design, develop and maintain data controls and governance for Financial Crime & Risk Management systems. Lead complex data initiatives, perform data profiling, root cause analysis, troubleshoot data pipelines, automate processes, integrate databases with analytics platforms, and collaborate globally to ensure data integrity for payments and transaction monitoring.

Lead and grow a Data Engineering team to modernize enterprise data platforms (Snowflake/Databricks), deliver secure scalable batch and real-time pipelines, enable DataOps/MLOps, establish CI/CD and IaC practices, monitor platform health, and drive strategic platform migrations and performance optimizations with cross-functional stakeholders.

Design, build, and automate network infrastructure and CI/CD pipelines; develop automated solutions (Ansible, Terraform, scripts, device APIs); triage and resolve automation issues; collaborate with security, corporate engineering, and partners to ensure scalable, reliable, and secure network access across cloud and physical environments.

Lead design, development, and deployment of large-scale Python-based Generative AI platforms and services. Drive architecture, stakeholder engagement, vendor partnerships, CI/CD, and governance. Manage multiple complex projects, mentor mid-level engineers, and ensure risk, monitoring, and integration across Citi business units.

The role involves designing, developing, and maintaining software solutions using Python, managing APIs, contributing to all phases of the development lifecycle, and mentoring junior engineers.

Support robotics research by modeling mechanical components and PCBs, developing and debugging robot code (ROS2/Python/C++), integrating sensors, actuators, and microcontrollers, and preparing technical reports, assembly procedures, and BOMs to advance prototypes toward manufacturing within a human-machine interaction research team.

Build voice-first multimodal prototypes and demos using on-device and cloud tools. Integrate speech toolkits (ASR/TTS), implement interaction logic combining audio, camera, and touch, run basic latency/usability tests, and document results while collaborating with researchers and designers.

Provide analytics support to business lines and finance through data analysis, automated workflows, BI reporting, advanced analytics and generative AI. Engage stakeholders, present findings to senior leaders, improve processes, and implement cloud-based data solutions.

Provide L1/L2 production support for Equities Derivatives pre-trade systems, troubleshoot distributed architectures, manage incident lifecycle, monitor intraday and end-of-day processes (risk, PnL, market data), escalate and collaborate with development teams, follow ITIL incident/problem/change processes, participate in on-call rotas, deployments, and disaster recovery testing.

Lead design, development, and maintenance of large-scale Python-based generative AI platforms and services. Collaborate with data science, technical, and business stakeholders to define architecture, deploy GenAI products, enforce coding standards and testing, mentor mid-level engineers, manage multiple projects, and ensure governance, risk, and controls for enterprise-grade AI solutions.

Lead and contribute to BSP-level embedded software for communication, networking, and video applications. Develop device drivers, manage kernel configurations, use Yocto/PetaLinux, integrate and debug FPGA SoCs and hardware, set architecture and technical direction, mentor teams, work with customers, and apply best practices for maintainable, high-quality code.

Support data integration, quality, analysis, and visualization efforts. Collaborate with cross-functional teams, build dashboards and reports (Tableau/Excel), perform exploratory analysis, and support data engineering and modeling to deliver business insights and recommendations.

Design and build high-performance SQL and Python data pipelines across PostgreSQL, BigQuery, Snowflake, and MongoDB. Implement RisingWave streaming and Kafka architectures, orchestrate workflows with Airflow on GCP, enforce data quality, deploy CI/CD for pipelines, and mentor teammates while collaborating with business stakeholders.

Lead development and maintenance of the core data platform: build performant pipelines, data warehousing, and ML infrastructure; partner with data scientists to produce production datasets; ensure data governance, quality, lineage, and accessibility; integrate cross-platform data sources; automate reporting and deliver stakeholder insights to enable data-driven decisions.

As a Product Engineer, you'll design and deploy scalable software solutions for a global SaaS platform, collaborating with teams, ensuring code quality, and resolving technical issues in an Agile environment.