Top Python Jobs in Toronto

Design, build, and maintain secure, high-performance back-end solutions in an Agile team. Provide technical leadership, design and review architectures, implement CI/CD deployments, use Databricks/PySpark and Azure data services, and improve performance monitoring and reliability.

Lead the architecture and development of Benevity’s user identity and access management platform. Design scalable authentication, authorization, SSO, federation, and identity lifecycle capabilities using Auth0 and cloud-native technologies. Establish zero-trust and least-privilege practices, guide platform modernization, create technical documentation and proofs of concept, collaborate with product and security teams, and mentor senior engineers.

Design and maintain automated testing frameworks for databases, ETL processes, data pipelines, and cloud data platforms. Develop Python and SQL test scripts, validate data integrity and transformations, perform source-to-target reconciliation, test PostgreSQL and StarRocks systems, and validate Tableau reporting. Integrate tests into CI/CD pipelines, identify data quality and performance issues, and collaborate with engineering and development teams in an Agile environment.

Validate Financial Crime Risk Management models for Trading Surveillance by performing validation testing and analysis, producing validation reports, communicating findings to stakeholders, and developing validation tests for advanced ML-based surveillance models while collaborating with Big Data developers and maintaining modeling best practices.

Leads analytics engagements for Small Business Banking, translating business needs into insights and strategic recommendations. Modernizes Power BI and Tableau reporting, develops migration roadmaps, and ensures data quality, governance, and compliance. Partners with data engineering and AI/ML teams on data curation, model monitoring, executive dashboards, and performance reporting. Provides analytics thought leadership, mentors team members, and promotes standardized, enterprise-grade reporting and visualization practices.

Develop embedded Linux software and GUIs for industrial controllers; implement industrial protocols (Modbus, BACnet, SNMP); support product lifecycle from development to production/service and write operational documentation.

Leads wealth analytics, reporting, automation, and data visualization solutions. Partners with stakeholders to define business needs, transform and integrate data, develop dashboards and recurring reports, automate processes, support UAT, resolve issues, and promote self-service analytics. Provides actionable insights, technical guidance, documentation, and training while ensuring alignment with risk management requirements.

Provides Level 2 production application support for mission-critical distributed systems. Builds automation, facilitates CI/CD and Infrastructure as Code, investigates incidents and performance bottlenecks, improves system resilience, and supports cloud, on-premises, and containerized environments. Collaborates with development and support teams using Agile and DevOps practices while contributing to reliable, secure, and optimized technology solutions.

Build and maintain marketing data pipelines connecting Salesforce, Marketo, and cloud data warehouses. Automate campaign reporting, develop SQL datasets and views, improve attribution and data quality, and support executive marketing pipeline reporting. The role also involves Salesforce and Marketo configuration, documentation, and AI-assisted analytics using tools such as Claude. Candidates will collaborate with Marketing Analytics, Demand Generation, and Marketing Operations.

Design and deploy vision and robotics systems for automated wire-harness production. Build perception pipelines (classical CV and/or ML), perform camera/hand-eye calibration, develop and tune robot motion for pick/place, routing, insertion, and termination, and deploy and harden systems on the production floor. Collaborate with mechanical, controls, and production teams to improve cycle time, yield, and reliability.

Lead design and delivery of scalable, cloud-native platform capabilities and ML-integrated applications. Oversee full SDLC, architecture, reliability, CI/CD, observability, and incident response. Provide technical leadership, mentor engineers, collaborate with stakeholders, and drive continuous improvement to support high-availability distributed fulfillment systems.

Lead large-scale backend platform initiatives, including shared frameworks, libraries, static analysis, service scaffolding, and developer tooling. Design scalable and reliable solutions used across backend services, influence engineering practices, partner with infrastructure, security, and product teams, and mentor engineers. The role requires technical leadership across complex projects and long-term platform investments.

Oversee OSFI capital reporting, guide analysts, and support regulatory capital initiatives. Lead automation and process optimization using Python, SQL, Power BI, Alteryx, Power Query, and Excel. Develop dashboards, analytical solutions, and reporting processes; improve data quality, controls, and efficiency. Analyze capital impacts of new products, support Basel and RWA calculator updates, interpret regulatory requirements, and advise business stakeholders on capital treatment and balance sheet optimization.

Leads strategic customer engagements involving agentic AI, AI-powered applications, application architecture, modernization, and cloud-native development. Designs solutions through architecture sessions, demonstrations, prototypes, proofs of concept, and pilots. Coordinates Microsoft technical teams and partners, creates repeatable technical assets, influences technical sales opportunities, coaches peers, and supports production deployment outcomes.

Designs and manages dashboards, reporting solutions, data pipelines, and self-service analytical tools for underwriting operations. Performs statistical analysis to identify trends, risks, performance drivers, and improvement opportunities. Translates business questions into recommendations, evaluates underwriting initiatives, ensures data quality, and communicates insights through visualization and storytelling. The role also supports AI and automation, mentors colleagues, and partners cross-functionally to improve measurable business outcomes.

Own the architecture, governance, and hands-on development of Rodan Energy’s Databricks lakehouse platform. Build and optimize ingestion and transformation pipelines across energy market, facility, and vendor data using Python, PySpark, SQL, Delta Lake, and Databricks tools. Establish medallion architecture, schemas, access controls, data quality standards, lineage, and monitoring. Collaborate with vendors, business stakeholders, and senior leadership while guiding platform standards and future capabilities.

Leads complex actuarial and strategic analytics initiatives in Personal Insurance pricing. Uses actuarial techniques, predictive modeling, statistical methods, and large datasets to identify opportunities, assess risks, improve pricing, and inform business strategy. Partners cross-functionally with pricing, underwriting, claims, distribution, and data science teams; presents recommendations to senior leaders; mentors junior staff; and drives innovative analytical solutions from problem definition through implementation.

Leads the technology vision, architecture, and engineering practices for enterprise data platforms, pipelines, integrations, and analytics solutions. Provides hands-on technical leadership across multiple teams, drives CI/CD, automation, testing, governance, modernization, and scalable data architecture. Integrates machine learning capabilities, translates business strategy into technical roadmaps, resolves complex data challenges, collaborates with stakeholders, and mentors engineering teams. Requires strong expertise in GCP, Databricks, Python, SQL, cloud and big data technologies, ETL/ELT, and data modeling.

Develop and maintain photonics Process Design Kits, including Python-based layout libraries, compact behavioral models, test structures, and automated verification pipelines. Validate models against silicon measurements through data fitting and statistical analysis. Collaborate with multidisciplinary engineering teams to support large-scale photonic integrated circuit tape-outs. The role requires advanced photonic device physics, circuit simulation, Python programming, layout automation, and experience with foundry PDKs and design verification.

Leads daily business unit operations in a manufacturing environment, ensuring production, budget, quality, safety, and delivery goals are met. Oversees cross-functional teams across quality, operations, engineering, scheduling, and planning. Identifies bottlenecks, drives continuous improvement, manages capital and efficiency initiatives, and partners with shared services, vendors, construction teams, and government stakeholders. Uses ERP systems, operational data, KPI dashboards, and process analysis to improve workflows and performance.

Design, build, deploy, and stabilize production software solutions directly with strategic customers. Develop applications, APIs, integrations, agents, data connectors, automation, and AI workflows. Own engineering workstreams, troubleshoot complex distributed systems, implement testing, CI/CD, infrastructure-as-code, observability, and operational runbooks. Collaborate with customer teams and Product to identify platform gaps, define reusable engineering patterns, and deliver reliable, secure, scalable solutions across networking, cloud, data, and AI environments.

Research Engineer developing human-robot interaction systems for consumer robots. The role spans robotics research and hands-on engineering across motion, perception, sensing, actuation, thermals, inference, firmware, hardware, datasets, and evaluation. Responsibilities include inventing and testing novel approaches, building real hardware and ML systems, deploying reliable low-latency solutions on edge devices, and documenting reproducible results. Candidates should demonstrate self-directed projects, end-to-end artifacts, hardware experience, ML deployment, and cross-layer technical adaptability.

Design, build, and maintain Azure-based data pipelines, data models, KPI marts, and reporting layers for financial and operational analytics. Translate business requirements into scalable solutions, perform reconciliation and root-cause analysis, implement data quality controls, execute QA and UAT, and document data flows and metric definitions. Collaborate with Finance, Business, Analytics, Technology, and infrastructure teams to deliver accurate, governed, production-ready datasets and improve automation and reliability.

Leads active quantitative equity portfolio management, including investment research, portfolio positioning, trading, risk management, performance oversight, and client communications. Develops systematic investment processes, oversees quantitative research and platform capabilities, and identifies improvements in data and analytics. Supports business development across institutional and retail channels, contributes to Canadian growth strategy, represents the investment process, and mentors junior team members.

Own backend services, APIs, SDKs, and operational tools for connected hardware and data-intensive workflows. Design reliable data models and asynchronous systems that handle retries, duplicate events, interrupted transfers, and device disconnections. Build telemetry and diagnostics, maintain production reliability and data integrity, test workflows end to end, and support authentication, versioning, documentation, monitoring, and backward compatibility.