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Added 5 mins ago
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Business Development Specialist (BDR)
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- Full-time
A team player who works well with sales, design and operations colleagues and welcomes feedback.
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Director, Product Management (Payments)
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Added 1 hour ago
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Added 1 hour ago
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Ipsos in Canada

Lead Data Engineer

Vancouver, BC, Canada

$130,000 to $140,000 CAD / year · Full-time

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Job details

Pay: $130,000 to $140,000 CAD / year
Job type: Full-time
Apply by: Dec 2, 2026
Experience: 8+ years of professional experience in data engineering, data platform engineering, or a closely related field, with demonstrated technical leadership on production systems.
Posting language: English
Posted: Nov 2, 2026

Original job description

Job Description

Title: Lead Data Engineer

Location: Any Ipsos Canada Location

Who We Are

Ipsos is one of the world’s largest research companies and currently the only one primarily managed by researchers, ranking as a #1 full-service research organization for four consecutive years. With over 75 different data-driven solutions, and presence in 90 markets, Ipsos brings together research, implementation, methodological, and subject-matter experts from around the world, combining thematic and technical experts to deliver top-quality research and insights. Simply speaking, we help the biggest companies solve some of their biggest problems, serving more than 5000 clients across the globe by providing research, data, and insights on their target markets. And, we’re proud to share we’ve received our Great Place to Work Certification in 2024, for the third year running!

ABOUT The Ipsos DataHub

The Ipsos DataHub is a uniquely positioned group within Ipsos. It is a next-generation data platform designed to unlock the full value of data across the organization. By bringing together information, technology, and expertise in a seamless and secure ecosystem, it empowers teams to move faster, think bigger, and deliver deeper, more meaningful insights. DataHub is at the heart of Ipsos’ vision to transform how data drives decisions, innovation, and impact for clients worldwide.

We’re looking for someone with a deep interest and expertise in data engineering and the dedication to apply that passion. We need someone with the technical expertise to expand and optimize our existing data pipeline and architecture. The ideal candidate will have experience using cloud-based platforms, like Google Cloud Services and AWS, to build and maintain serverless data pipelines to efficiently process and warehouse large scale datasets. The role also requires conscientious attention to detail, an ability to work well on a small team, and a self-starter approach to problem solving and debugging.

What You Can Expect To Be Doing

Lead the architecture, design, coding, testing, and delivery of cloud-based data pipelines and platform components that process and store large-scale datasets.
Establish engineering standards, reusable patterns, and technical guardrails for data ingestion, transformation, orchestration, storage, and serving.
Design and optimize data warehouses and distributed data systems for scalability, security, reliability, performance, and cost efficiency.
Provide hands-on technical leadership through solution design, code reviews, debugging, production support, and mentorship of data engineers.
Own production readiness and reliability practices for the data platform, including service-level indicators/objectives (SLIs/SLOs), observability, monitoring, alerting, capacity planning, and failure-mode analysis.
Lead incident response for data-platform and pipeline disruptions; drive root-cause analysis, blameless post-incident reviews, and corrective actions that reduce recurrence and operational toil.
Improve software delivery and operations through automated testing, CI/CD, infrastructure as code, runbooks, release controls, and operational tooling.
Drive the migration of development code into production and ensure systems are supportable, maintainable, well-documented, and production-grade.
Partner with internal and external stakeholders to translate business and project needs into technical architecture, delivery plans, and clear trade-off decisions.
Continuously troubleshoot and improve existing infrastructure and codebases, and responsibly incorporate AI/LLM-based tools where they improve engineering productivity and quality.

This might be the job for you if you have:

8+ years of professional experience in data engineering, data platform engineering, or a closely related field, with demonstrated technical leadership on production systems.
Bachelor's degree in computer science or a related field required; master’s degree or higher preferred.
Proficiency in Python and advanced working knowledge of SQL.
Strong hands-on experience with GCP services, including BigQuery and GCS; familiarity with other cloud platforms is an asset.
Hands-on SRE or production-engineering experience, including observability, SLIs/SLOs, monitoring and alerting, incident response, post-incident reviews, reliability automation, and operational readiness.
Experience with CI/CD and infrastructure-as-code practices; experience with tools such as Terraform is preferred.
Prior success designing, deploying, and operating large-scale data pipelines and distributed storage/compute systems in production environments.
Strong understanding of production failure modes, performance tuning, capacity planning, data quality, and disaster-recovery/recoverability concepts.
Experience with collaboration tools (e.g. Atlassian suite) and version control systems (e.g. Git).
Experience incorporating AI/LLM-based tools into data engineering workflows, with demonstrated ability to critically evaluate outputs and apply sound engineering judgment to accept, adapt, or reject suggestions.
Strong technical communication skills and the ability to explain complex engineering concepts, influence technical decisions, and work effectively in a highly collaborative, consensus-oriented environment.
Strong attention to detail, excellent time-management skills, and a track record of mentoring engineers and raising engineering standards across a team.

In accordance with Ontario & British Columbia law, the estimated base salary range for this role is $130,000 - $140,000 CAD. Your final base salary will be determined based on several non-discrimatory factors which may include but are not limited to location, work experience, skills, knowledge, education and/or certifications.

If you don’t meet 100% of the requirements, we encourage all who feel they might be a fit for the opportunity to apply. We may consider a variety of backgrounds for a particular role and are also committed to considering candidates for available positions throughout our organization, not just the one you’re applying to!

What’s In It For You

At Ipsos you’ll experience opportunities for Career Development, an exceptional benefits package (including generous PTO, healthcare plans, wellness benefits), a flexible workplace policy, and a strong collaborative culture.

To find out more about all the great reasons to work at Ipsos, how we’re making an impact around the world, and more about our benefits and employee programs, please visit: Why Work at Ipsos | CA

Inclusive Workplace Commitment

Ipsos recognizes the necessity of building an inclusive culture that values each employee’s individuality and diverse perspectives. For more than 40 years, our mission has been to generate and analyze data about society, markets, brands, and behaviors to provide our clients with the insights that elevate their understanding of the world. This could not be fulfilled without Ipsos’ diverse employees who compile and analyze this data - they are the essence of who we are and what we do.

We are committed to providing equal opportunity to all employees, creating an environment that promotes inclusion, and enabling employees from all walks of life to flourish. Ipsos encourages our employees to act in a respectful and responsible manner, in line with code of best practices concerning diversity and inclusion, human rights, equality, and civility for every individual.

Ipsos is An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or any other protected class and will not be discriminated against on the basis of disability.

#IpsosCanada

About Us

Ipsos is one of the world’s largest research companies and currently the only one primarily managed by researchers, ranking as a #1 full-service research organization for four consecutive years. With over 75 different data-driven solutions, and presence in 90 markets, Ipsos brings together research, implementation, methodological, and subject-matter experts from around the world, combining thematic and technical experts to deliver top-quality research and insights. Simply speaking, we help the biggest companies solve some of their biggest problems, serving more than 5000 clients across the globe by providing research, data, and insights on their target markets. And we are proud of our continuous efforts in making Ipsos the best place to work!

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More about this job

Responsibilities

Lead the design, development, and operation of scalable cloud data pipelines and platform components, establishing engineering standards and ensuring reliability, security, performance, and cost efficiency. Provide technical leadership through mentoring, production support, incident response, stakeholder collaboration, and improvements to delivery practices and platform operations.

Requirements

Requires 8 or more years of data engineering or related experience, a bachelor's degree in computer science or a related field, strong Python and SQL skills, and hands-on experience with GCP data services and production-scale data systems. Candidates should also bring SRE and operational reliability experience, CI/CD and infrastructure-as-code knowledge, strong communication skills, and a record of technical leadership and mentoring.

Skills

Data Engineering
Python
SQL
Google Cloud Platform
BigQuery
Google Cloud Storage
AWS
Data Pipelines
Data Warehousing
Distributed Systems
Site Reliability Engineering
Observability
Incident Response
CI/CD
Infrastructure as Code
Terraform

Benefits

Generous Paid Time Off
Healthcare Plans
Wellness Benefits
Career Development
Flexible Workplace Policy

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Data Platform Engineering
Python
SQL
Google Cloud Platform
BigQuery
Google Cloud Storage
AWS
Cloud Computing
Serverless Data Pipelines
Data Ingestion
Data Transformation
Data Orchestration
Data Warehousing
Distributed Storage
Distributed Compute
Site Reliability Engineering
SLIs
SLOs
Observability
Monitoring
Alerting
Incident Response
Root-Cause Analysis
CI/CD
Infrastructure as Code
Terraform
Git
Atlassian Suite
AI/LLM Tools

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