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Manager Data Engineering Jobs in Toronto, ON (NOW HIRING)

Hire DigITalent

Data Engineering Lead

Toronto, ON · On-site

We are seeking a senior, hands-on Data Engineering Lead for one of our clients to oversee ... Optimize cloud data platform storage patterns, lifecycle policies, and cost management.

Dentsu Aegis Network

Manager, Data Architect

Toronto, ON · On-site

CA$90K - CA$105K/yr

The Manager, Data Architect is accountable for the end-to-end architecture, technical direction ... Qualifications * 5+ years in data engineering, analytics engineering, BI architecture, or related ...

Td

Data Platform Engineering Manager

Toronto, ON · On-site

CA$115K - CA$163K/yr

The Data Platform Engineering Manager role is responsible for designing, building, and operating the enterprise technology reference data platform that serves as the foundation for technology ...

Scotiabank

Data Engineer

Toronto, ON

Build and optimise data pipelines using Azure cloud services, Databricks, Spark, Unity Catalog, dbt, and related data engineering tools. * Work with stakeholders, product managers, architects, and ...

McKesson

Lead, Data Engineer

Mississauga, ON · On-site +1

CA$122K - CA$162K/yr

Define and uphold engineering standards, patterns, and best practices aligned with enterprise data ... Partner with Product Managers, Data Scientists, Analysts, and business stakeholders to translate ...

Netlight

Data Engineering Consultant

Toronto, ON · On-site

CA$95K - CA$120K/yr

Netlight has been awarded several times for profitable growth and management, as a top employer ... We build solutions across diverse domains - backend, frontend, cloud, mobile, data engineering ...

McKesson

Lead, Data Engineer

Mississauga, ON · On-site +1

CA$122K - CA$162K/yr

Define and uphold engineering standards, patterns, and best practices aligned with enterprise data ... Partner with Product Managers, Data Scientists, Analysts, and business stakeholders to translate ...

MCKESSON

Lead, Data Engineer

Mississauga, ON · Remote

CA$122K - CA$162K/yr

Define and uphold engineering standards, patterns, and best practices aligned with enterprise data ... Partner with Product Managers, Data Scientists, Analysts, and business stakeholders to translate ...

TMX Group

Big Data Engineer

Toronto, ON · Hybrid

Engineering Excellence: Adhere to development best practices, ensuring meticulous code management ... Data Platforms: Proven experience working with Snowflake. * Programming: Proficiency in Python ...

Td

Data Engineer III

Toronto, ON · On-site

CA$96K - CA$136K/yr

Integrate billing, usage, tagging, metadata, CMDB, application, owner, finance, contract, and ... Partner with Engineering Analytics to deliver enterprise dashboards, automated alerts ...

GEI Consultants

Data Engineer

Concord, ON

CA$90K - CA$150K/yr

This includes building ingestion pipelines, managing data stores, implementing quality and ... Minimum Qualifications * 4+ years of data engineering experience, with demonstrated ability to ...

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Showing results 21-40

All JobsData Engineering JobsManager Data Engineering JobsManager Data Engineering Jobs in Toronto, ON

Manager Data Engineering information

See Toronto, ON salary details

$77.8K

$123.5K

$214.2K

How much do manager data engineering jobs pay per year?

As of Sep 3, 2026, the average yearly pay for manager data engineering in Toronto, ON is $123,507.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,865.00 and $129,790.00 per year, depending on experience, location, and employer.

What are the roles and responsibilities of a manager data engineering?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

What are the key skills and qualifications needed to thrive as a manager data engineering?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

How does a manager data engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.

What is the difference between Manager Data Engineering vs Data Engineer?

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the most commonly searched types of Data Engineering jobs in Toronto, ON?

The most popular types of Data Engineering jobs in Toronto, ON are:

What are popular job titles related to Manager Data Engineering jobs in Toronto, ON?

For Manager Data Engineering jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Manager Data Engineering jobs in Toronto, ON look for?

The top searched job categories for Manager Data Engineering jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Manager Data Engineering jobs?

Cities near Toronto, ON with the most Manager Data Engineering job openings:

Manager Data Engineering jobs near you
Infographic showing various Manager Data Engineering job openings in Toronto, ON as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $123,507 per year, or $59.4 per hour.

Data Engineering Lead

Hire DigITalent

Toronto, ON • On-site

Full-time

Posted 23 days ago

Job description

We are seeking a senior, hands-on Data Engineering Lead for one of our clients to oversee enterprise data engineering, platform development, and team mentorship. In this role, you will lead a cross-functional team to design, build, and operate secure, highly scalable end-to-end ETL/ELT pipelines, manage cloud infrastructure, and establish engineering excellence across the organization. We are looking for someone that is passionate about all things data, but also enjoys team management and helping their peers grow, develop, and work towards various organization goals as a cohesive team.

Technical Leadership & Pipeline Engineering

  • Pipeline & Architecture: Lead the design, operation, and optimization of scalable ETL/ELT pipelines and orchestration workflows. Define and maintain data architecture, modeling standards, governance, and data lineage practices.
  • Engineering Standards: Establish and enforce team best practices for code review, version control, testing, and CI/CD deployment to ensure high-quality, well-documented outputs.
  • Platform & Cost Optimization: Monitor pipeline health and infrastructure performance to lead rapid incident diagnosis. Optimize cloud data platform storage patterns, lifecycle policies, and cost management.
  • Continuous Improvement: Automate manual workflows, actively reduce technical debt, and evaluate emerging tools and technologies to boost team productivity.

Required Experience & Background

  • Professional Experience: 8+ years of progressive data engineering/platform experience, including 3+ years in a technical leadership, team lead, or people management role.
  • Industry Background: Strong preference for candidates coming from a Retail or E-commerce environment.
  • Cloud & Platform Mastery: Proven expertise with enterprise-scale cloud data platforms. Hands-on Snowflake experience is required, alongside working knowledge of Azure or GCP.
  • Agile Delivery: Deep experience guiding technical teams through agile delivery frameworks and modern DevOps workflows.

Technical Skills & Competencies

  • Languages & Frameworks: Expert-level SQL and Python. Deep hands-on experience with orchestration and deployment tools (e.g., Apache Airflow, Azure Data Factory, Git, and CI/CD frameworks).
  • Data Design: Strong grasp of data modeling methodologies (Dimensional, Star Schema, Data Vault) and data observability/quality frameworks.
  • Soft Skills: An exceptional communicator who can confidently translate technical concepts for business stakeholders, navigate ambiguity, and hold a team accountable for high-quality, on-time delivery.
  • SAP Integration: Experience extracting/transforming data from SAP modules is ideal