Top Tech Jobs & Startup Jobs in Toronto

Conduct advanced analytics and statistical modeling for Retail Media Network campaigns, measuring attribution, ROAS, incrementality, and advertising effectiveness. Build predictive models, dashboards, reporting solutions, and automated analytical workflows using SQL, BigQuery, Python, Tableau, and Looker. Translate complex findings into actionable recommendations, manage analytical projects, document methodologies, collaborate with clients, and mentor junior analysts.

Develop and maintain Tableau and Looker dashboards, campaign performance reports, and automated reporting workflows. Analyze large datasets using BigQuery, SQL, Python, and statistical techniques to identify trends and actionable insights. Ensure data quality through profiling, cleansing, validation, and reconciliation. Collaborate with stakeholders to define KPIs, translate requirements into scalable analytical solutions, communicate findings, document workflows, and manage deliverables from development through deployment and maintenance.

Support the SVP and Strategy team with business development initiatives, sales prospecting, market research, customer and competitor analysis, sales presentations, social media content, email campaigns, and lead generation. The intern will help identify new market opportunities, target accounts, decision-makers, and use cases while contributing to pipeline growth and strategic positioning.

Creates graphics, short-form content, pitch decks, social media assets, marketing materials, and internal communications. The intern helps maintain brand consistency, follows and develops visual templates, supports company and client storytelling, contributes to the content calendar, and tracks design and social media trends. The role requires a portfolio, familiarity with design tools, strong visual skills, communication abilities, organization, and the ability to manage multiple deadlines.

Welcomes visitors, manages front-desk communications, schedules meetings, maintains records, handles mail and courier deliveries, manages office supplies, coordinates vendors and building maintenance, supports basic bookkeeping, and assists with administrative projects and events. The role is fully onsite in downtown Toronto and requires strong organization, communication, discretion, multitasking, and Google Workspace proficiency.

Client-facing Product Manager supporting an enterprise Quality AI initiative. Responsibilities include gathering requirements, coordinating business and technical teams, evaluating vendor deliverables, shaping AI-enabled workflows and interfaces, managing UAT and launch readiness, tracking risks and dependencies, and defining KPIs to measure business value. The role bridges Quality stakeholders, data and analytics teams, IT, and implementation vendors to deliver reliable, transparent, and user-friendly AI solutions.

Lead client-facing data architecture initiatives from discovery through production. Design Azure Databricks and Delta Lake platforms, establish medallion architecture, governance, modeling, ingestion, quality, and CI/CD standards, and guide distributed engineering teams. Review architectures, code, pipelines, and data models while advising stakeholders on performance, cost, security, and scalability. Provide hands-on expertise with SQL, Python/PySpark, Airflow, dbt, Unity Catalog, and Databricks-native ingestion technologies.

Design and deliver enterprise GenAI and agentic AI solutions for Fortune 500 clients. Lead discovery sessions, architecture design, client presentations, and technical evaluations while building production-ready applications using LLMs, RAG, agents, Python, LangChain, LangGraph, and Databricks. Integrate structured and unstructured data with enterprise systems, establish evaluation and observability practices, implement responsible AI controls, and support scalable, secure production deployments.

Lead design, architecture, and delivery of enterprise-scale data platforms using Databricks and Spark. Architect Lakehouse solutions, build ETL/ELT pipelines, implement IaC and CI/CD, ensure data governance and security, mentor engineers, and partner with Fortune 500 clients from discovery through production.

Design, build, and scale data-driven platforms and systems, focusing on backend and frontend engineering, integrations, and AI capabilities.