Top Python Jobs in Montreal

Develop and maintain Java and Python software for Elsevier’s Research Data Platform. Responsibilities include writing, debugging, reviewing, and improving code; harvesting and transforming large datasets; and supporting data products. The role involves data modeling, manipulation, DevOps practices, and technologies such as Kafka, Kubernetes, Databricks, Airflow, and Iceberg. Professional English and French communication and residence in the Montreal area are required.

Develop and maintain Java and Python software for Elsevier’s Research Data Platform. Harvest, transform, and process large datasets supporting data products. Contribute code, debugging, code reviews, data modeling, and software development activities while working with technologies such as Kafka, Kubernetes, Databricks, Airflow, Terraform, and Iceberg. The role requires English and French proficiency and is based in Montreal.

Build and maintain Supabase’s public Python SDK across database, authentication, storage, realtime, and edge functions. Develop natural sync and async APIs, manage typing, packaging, testing, release automation, documentation, and issue triage. Collaborate with cross-functional teams and open-source contributors, support multiple Python environments, maintain WebSocket functionality, and design migration paths for API changes. Work autonomously in a remote, asynchronous environment while making the SDK accessible to developers and AI coding agents.

Assist with designing, coding, testing, debugging, and maintaining full-stack software features for home healthcare intake and marketplace products. Use GenAI tools, write automated tests, investigate bugs, participate in code reviews and pair programming, and learn CI/CD, Docker, containerization, and monitoring practices while collaborating with technical and non-technical teammates.

Develop and optimize Python backend services that automate financial forecasting and recurring processing. Build and evolve data pipelines and distributed architectures using SQL, DataIQ, Databricks, and Snowflake. Collaborate with engineering, data, and infrastructure teams on integrations, architecture, testing, CI/CD, monitoring, performance, reliability, and security. Work with Teradata and legacy platforms while delivering solutions in a regulated financial environment.

Design, develop, test, deploy, and maintain Python-based solutions for Kubernetes configuration management and Kafka administration. Build low-latency distributed systems, elastic cloud capabilities, REST APIs, and CI/CD pipelines supporting real-time trading data. Participate across the full project lifecycle, including proofs of concept, technical design, coding, implementation, and release. Support security infrastructure and develop encryption key management solutions while collaborating effectively with project teams.

Build backend services and APIs primarily in Python, with frontend contributions in React and TypeScript. Develop experimentation platforms, near-real-time data ingestion and processing, AI-powered workflows, partner integrations, RBAC, and other product capabilities. Collaborate with product managers, designers, data scientists, and senior engineers while delivering production-ready features across backend, frontend, pipelines, and infrastructure.

Lead backend-focused software architecture and development for data-intensive products, including experimentation platforms, near-real-time ingestion, AI workflows, integrations, APIs, and distributed systems. Partner with product, design, and data science teams to translate ambiguous needs into scalable production solutions. Contribute across frontend, pipelines, and infrastructure, while mentoring engineers, conducting design reviews, and setting technical direction.

Own the architecture and technical direction of Northbeam’s data ingestion and integration platform. Lead event-driven and batch processing decisions, establish standards for observability, freshness, and failure handling, and guide cross-functional platform design. Mentor engineers, conduct design reviews, influence teams without direct authority, and drive foundational platform improvements. The role requires deep Python and SQL expertise, cloud data warehouse experience, scalable API-based ETL design, orchestration, and containerized infrastructure experience.

Build and maintain secure, scalable Flow Registry features for GitLab’s agentic platform using Python, LangChain, and LangGraph. Design GraphQL and REST APIs, improve automated testing, optimize PostgreSQL-backed applications, and collaborate across backend, frontend, product, UX, and AI teams. Participate in Tier 2 on-call support, troubleshoot production issues, improve observability, and contribute to responsible AI integration in GitLab’s remote, asynchronous environment.

Leads technical design and hands-on development of customer integrations, connector automations, custom exports, workflow flows, and file-based interfaces. Owns data accuracy and auditability, mentors developers across teams, guides complex cross-functional projects, and represents Engineering in customer discussions. Identifies repetitive customer-specific work for productization and automation, adopts AI engineering tooling, and feeds field insights into Product and Solution Architecture.

Build and lead across Tetrix’s SaaS product, data pipelines, AI agents, and telemetry infrastructure using Python and JavaScript. Set technical direction, make architectural decisions, shape product strategy, collaborate with clients, establish secure and scalable engineering practices, mentor engineers, and help build a high-performing team.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from ad platforms, order systems, and real-time events. Ensure reliability, observability, and maintainability across event-driven and batch architectures, implement authentication flows, optimize data workflows in a cloud-native environment, and collaborate with product, infrastructure, and data teams to onboard new sources.

The Backend Software Engineer will develop and maintain backend systems for data processing related to coffee farming, utilizing Python and PostgreSQL. Responsibilities include feature development, problem-solving, and adapting systems to regulatory changes while ensuring system resilience.

Lead end-to-end engineering initiatives for customer-facing features in a fast-paced startup. Build and maintain backend and frontend systems, design and evolve GraphQL APIs, debug production issues, participate in on-call rotation, and collaborate cross-functionally with product, policy, and commercial teams to deliver high-quality, scalable software for battery asset operations and project simulation.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

The Python Engineer will write maintainable Python software, lead technical initiatives, collaborate globally, and contribute to community engagement at Canonical.

Develop and enhance features for EnrollWise, contribute to a scalable software architecture, review code, collaborate on design and technical feasibility, and maintain software quality.

As a Software Engineer, you will develop and maintain the Tally software stack, enhance robot navigation and autonomy, and support CI/CD processes.

Design, implement, test, and maintain full‑stack features in a SaaS product. Provide technical leadership, mentor peers, influence product technical roadmap, monitor production, improve testing practices, and participate in future on‑call rotations.

Design and build distributed backend systems, microservices, and near-real-time data ingestion and processing. Scale an incrementality experimentation platform, add AI-powered workflows, extend data integrations and partner exports, and contribute frontend components as needed to deliver end-to-end product features.

Build and maintain Python tools for web scraping, automation, integrations (Airbnb, marketplaces), ad automation, chatbots (Chatwoot), workflow automation (Spiffworkflow), automated tests, and data analysis.

Build and scale backend systems for a B2B SaaS platform, including data pipelines, AI agents, telemetry and document/data extraction; contribute to product direction, work with clients, champion best practices, and mentor team members.

Build and maintain the SaaS product, data pipelines, AI agents, and telemetry; contribute to product and tech strategy; work with customers; set engineering best practices and mentor teammates.