Top Python Jobs in Toronto

The role involves leading financial analysis for technology spend, designing data models, developing visualizations, and ensuring data quality, while collaborating with internal stakeholders across the company.

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.

The Data Engineer will develop and maintain data pipelines, ensure data quality, and collaborate with business teams to implement insightful data solutions.

Manage financial analysis, oversee annual budget and forecasting, provide insights for decision-making, and lead a team of junior analysts.

Design, build, and optimize Databricks Lakehouse data platforms and production ETL/ELT pipelines using PySpark, Delta Lake, and medallion architectures. Implement governance with Unity Catalog, manage CI/CD and IaC, optimize Spark and clusters for performance/cost, collaborate with data science and analytics teams, and mentor engineers while driving observability and security/compliance practices.

Design, build, and optimize Snowflake-based data platforms: ingest and model data, implement ELT pipelines, enforce governance and security, tune performance, build CI/CD, enable near-real-time solutions, mentor engineers, and collaborate with stakeholders.

Design, deploy, and maintain end-to-end ML-driven risk solutions at scale to detect and prevent fraud, abuse, and credit risk. Lead technical decisions, build ML tooling and processes, apply state-of-the-art models and third-party data, investigate emerging risk patterns, and collaborate with platform and cross-functional teams to ensure reliable real-time model operation.

Drive CI efforts, ensuring reliable and scalable development pipelines, while mentoring other engineers and improving developer productivity through tooling and automation.

Design, deploy, and maintain end-to-end ML risk solutions at scale to detect and prevent fraud, merchant risk, and credit loss. Partner with cross-functional teams, lead technical decisions, build ML tooling, monitor models in production, and investigate emerging abuse patterns to improve detection and decisioning.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Design, build, and operate enterprise-scale multi-cloud infrastructure (Azure primary, GCP, AWS exposure). Own landing zones, Terraform modules, production AKS/GKE Kubernetes, Vault secrets, hybrid networking, CI/CD pipelines, monitoring, DR, and automation (Ansible, Python/Bash). Mentor engineers, document runbooks, and collaborate with security, application teams, and leadership to ensure secure, reliable, cost-optimized cloud platforms.

Lead full-stack design and development for Capital One's travel portal across front-end and back-end. Own architecture, apply HLD methodology, establish engineering best practices, mentor junior engineers, and improve developer experience while working through the SDLC on fault-tolerant, multi-platform systems.

Lead backend development for Capital One's travel portal across the full SDLC. Own technical design and architecture, drive engineering best practices, improve developer experience and internal tooling, mentor junior engineers, and deliver fault-tolerant, cross-platform services using cloud-native technologies.

Lead a global End User Services team delivering 24/5 support for GitLab's SaaS toolstack. Own EUS strategy, incident/request/problem/change management, SLAs, CSAT, asset and SaaS lifecycle, and scale support via automation, self-service, and AI. Partner cross-functionally with People, Security, IT Engineering, Workplace, Finance, and Procurement to optimize onboarding, tooling, vendor relationships, and operational KPIs.

The Strategic Finance Lead will drive financial strategy, build financial models, provide analytics to support revenue growth, and collaborate with cross-functional teams.

The Senior Software Engineer II will design automated reliability systems, improve tooling for incident management, and enhance observability infrastructure, contributing to operational excellence across engineering teams.

As a Senior Software Engineer on the AI Platform, you'll develop scalable AI systems, focusing on backend services, workflows, and integrations, partnering with cross-functional teams.

Lead a data science team to design, train, evaluate, and implement ML models using Python, AWS, and agentic AI. Partner with cross-functional stakeholders, translate technical work to business outcomes, manage talent, and evaluate new technologies for digital banking risk and decision-making.

The Senior Data Engineer will develop and maintain data platforms on Google Cloud, optimize data pipelines, and support Data Science teams in model training and analytics, collaborating closely across departments.

The role focuses on extracting, cleaning data, building and maintaining machine learning models, and optimizing business strategies using data science methodologies.

As a Senior Machine Learning Engineer, you'll design and develop workflows utilizing vision-language models, manage data pipelines, and collaborate with multiple teams to enhance model accuracy and efficiency.

The Senior Analyst, Portfolio Strategy will provide insights to drive business growth, manage portfolio risk, and analyze pricing and profitability.

Drive post-silicon bring-up, characterization, qualification, and productization of advanced-node bitcoin mining ASICs from first silicon to mass production. Develop and maintain ATE test programs and screening strategies, perform PVT characterization and DOE, analyze wafer/package/ system data to improve correlation, yield, and system performance, and collaborate with foundry, OSAT, design, firmware, and manufacturing partners to implement corrective actions and production-ready processes.

Design and implement core pricing services, improve APIs, lead design reviews, ensure system reliability, and mentor junior engineers.

Design, build, and tune cloud-native detection and response capabilities in Microsoft Azure. Develop Sentinel analytics, KQL queries, SOAR/Logic Apps playbooks, integrate security tooling across Azure and M365, translate threat intelligence into detections, and collaborate with an MDR partner and internal teams to improve SOC processes and automated response workflows.