Closed listing
Senior Data Engineer
- Vancouver, BC, Canada
Full-time
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Full-time
- Closing date
- Experience
- 5+ years of professional experience as a data engineer
- Posting language
- English
- Posted
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Archived listing. The details below describe a past opening.
Title: Senior Data Engineer
Location: Any Ipsos Canada Location
Who We Are
Ipsos is one of the world's largest research companies and the only one primarily managed by researchers. Ranked the #1 Most Innovative Market Research Supplier by Greenbook’s GRIT report for four consecutive years, we operate in 90 markets, offer more than 75 data-driven solutions, and serve over 5,000 clients worldwide. Our research, methodological, implementation, and subject matter experts help organizations solve complex business challenges through data-driven insights and evidence-based decision-making. We're proud to have been named one of Forbes' America's Best Employers for Company Culture in 2025, Forbes' America's Best Employers for Women in 2026 and recognized by Newsweek as one of the World’s Most Trustworthy Companies in 2026.
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
- Design, code, and test cloud-based data pipelines to process and store large-scale datasets.
- Develop and maintain data warehouses to efficiently store large, complex datasets in a cost-optimal manner.
- Ingest and assemble data from various disparate sources using a variety of tools, including Python and SQL.
- Work with internal/external stakeholders to identify and understand needs and project goals.
- Drive the migration of development code into production, providing technical assistance and guidance to refine and optimize processes.
- Troubleshoot and improve existing infrastructure and codebases.
- 5+ years of professional experience as a data engineer
- Bachelor's degree in computer science or a related field required, master’s degree or higher preferred
- Proficiency in Python & advanced working knowledge of SQL
- Experience incorporating AI/LLM-based tools into data engineering workflows, with demonstrated ability to critically evaluate AI outputs and apply sound engineering judgment to accept, adapt, or reject suggestions.
- Strong technical communication skills
- Experience with collaboration tools (e.g. Atlassian suite) and version control systems (e.g. Git).
- Strong hands-on experience with GCP services (e.g. BigQuery, GCS); familiarity with other cloud platforms is an asset.
- Comfortable working in a highly collaborative, consensus-oriented environment.
- Prior success designing and deploying data pipelines in large-scale production environments.
- Strong eye for detail, ability to communicate scientific concepts both in written form and verbally, and excellent time-management skills.
- Large dataset manipulation. Experience in distributed storage and computing.
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!
More about this job
Responsibilities
Design, build, test, and optimize cloud-based data pipelines and cost-efficient data warehouses for large, complex datasets, using Python, SQL, and cloud services. Ingest data from disparate sources, collaborate with stakeholders, support code deployment to production, and troubleshoot existing infrastructure and codebases.
Requirements
Requires at least five years of professional data engineering experience, a bachelor's degree in computer science or a related field, proficiency in Python, and advanced SQL knowledge; a master's degree or higher is preferred. Candidates should have hands-on GCP experience, production-scale pipeline experience, familiarity with AI/LLM tools, version control and collaboration tools, and strong communication, problem-solving, and organizational skills.
Skills
- Python
- SQL
- Google Cloud Platform
- BigQuery
- Google Cloud Storage
- AWS
- Data Pipeline Engineering
- Data Warehousing
- Cloud Computing
- Serverless Data Pipelines
- Large-Scale Data Processing
- Distributed Storage and Computing
- AI and LLM Tools
- Git
- Atlassian Suite
- Troubleshooting
Benefits
- Generous Paid Time Off
- Healthcare Plans
- Wellness Benefits
- Career Development
- Flexible Workplace Policy
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Engineering
- Science & Research
Keywords
- Data Engineering
- Data Pipelines
- Data Warehousing
- Python
- SQL
- Google Cloud Platform
- BigQuery
- Google Cloud Storage
- AWS
- Cloud Computing
- Serverless Architecture
- Large-Scale Datasets
- Data Ingestion
- Distributed Storage
- Distributed Computing
- AI Tools
- Large Language Models
- Production Environments
- Git
- Atlassian Suite
- Data Migration
- Infrastructure Optimization
- Troubleshooting
- Market Research
- Stakeholder Collaboration