Lead Data Engineer

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 #1full-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’reproud tosharewe’vereceived our Great Place to Work Certification in 2024, for thethird year running!

ABOUT The Ipsos Data Hub
The Ipsos Data Hub 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. Data Hub 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…