Top Data Engineer Jobs in Toronto

The Data Engineer will develop scalable big data solutions, collaborate with internal teams, and optimize data pipelines to support various business needs.

As a Growth Data Engineer, you will build and manage marketing data and attribution systems, ensuring reliable data flow and accurate measurement of acquisition efforts. The role involves collaboration across product, marketing, and data teams with a focus on optimizing campaign performance.

The Founding Data Engineer will design and build OpenArt's core data platform, ensuring data reliability, consistency, and scalability to support leadership and product metrics.

The Data Engineer will architect and implement advanced analytics capabilities, manage data pipelines, and optimize data processing using AWS cloud and various analytical tools.

The Data Engineer will develop and deliver technical projects focused on data integrity, security, and scalable analytics solutions, working closely with team members and ensuring effective data pipelines and infrastructure.

The Senior Staff Software Engineer will architect Affirm's lakehouse analytics platform, implement data governance, mentor engineers, and collaborate cross-functionally to optimize data infrastructure and solutions.

Build and operate scalable data ingestion, transformation, and connector frameworks; design and maintain a knowledge-graph-based data fabric; normalize and vectorize enterprise data for LLM/AI workflows; implement governance, lineage, access controls, and secure APIs to serve ML/agent pipelines.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Build and maintain end-to-end ELT pipelines, design scalable data models, create APIs for data/ML serving, and collaborate with engineering, data, and business teams to deliver core data infrastructure.

As a Data Developer, you'll build and optimize data pipelines, collaborate with cross-functional teams, support data architecture, and ensure data quality along with mentoring on best practices.

Own cloud operational health, architecture intelligence, and cost optimization. Analyze cloud spend, build dashboards/reporting, enforce governance, review architecture for cost impact, and translate technical findings for engineering, finance, and executives.

Seeking an experienced Data Engineer to design and maintain data pipelines and infrastructure, collaborating with data scientists and stakeholders.

The Guidewire Data Engineer will design schemas in Snowflake, develop ETL processes, optimize SQL queries, and integrate Guidewire with data platforms.

This role involves designing and developing scalable data solutions, automating tasks, and collaborating with teams to deliver business value. Responsibilities include strong database development using SQL and Python, as well as leading innovative projects and ensuring compliance.

Design, build, and optimize cloud-based data platform components: ingest and transform varied datasets, create metadata-driven pipelines and data APIs, support AI/ML infrastructure, implement monitoring and metrics, and improve data processes to enable analytics and operational systems.

As an Intermediate Data Engineer, you will develop data infrastructure and products, collaborate with diverse teams, and enhance technical quality across the data team.

As a Sr. Data Engineer, you'll design and manage data pipelines, enhance data quality, and leverage AI to streamline operations, driving the success of our AI growth platform for real estate.

As a Data Engineer, you'll develop storage infrastructure, collaborate with teams, implement data systems, and contribute to product strategy. You'll work with advanced AI systems and process production-grade data.

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.

The Senior Data Developer will build and operate a CDC streaming platform, managing Kafka and Flink infrastructure, ensuring reliability, and creating CI/CD pipelines for data streaming applications.

The Data Engineer will build scalable data processing tools, collaborate with teams, enhance developer experience, and support AI interactions with data infrastructure.

The Intermediate Data Engineer designs and builds scalable data solutions, manages data ingestion and pipelines, and supports BI initiatives. Responsibilities include collaborating with stakeholders, ensuring data integrity, and mentoring team members while adhering to best practices in data engineering.

Own and maintain data platform infrastructure: provision Snowflake via Terraform, build CI/CD for dbt, implement data quality and observability, extend the OpenMetadata catalog, create developer tooling and reproducible environments, and ensure secure, production-ready data pipelines.

Design, build, and maintain scalable data pipelines and architectures supporting analytics, AI, and ML. Implement dbt models, orchestrate workflows with Airflow (MWAA), develop Snowflake-based data warehouses, write Snowflake SQL and Python/Shell pipelines, create Power BI reports, and support AWS-native production deployments while following global data engineering standards.