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Data Engineer Manager Jobs in Quebec (NOW HIRING)

Artefact

Sr Data Analyst

Montreal, QC

About the job Do you think like a management consultant, thrive in a startup environment, and can't ... Programming: Jupyter, VS code, Github * Programming languages: Python, R, SQL * Tool * * Cloud ...

AlayaCare

Staff Data Developer

Montreal, QC

As a senior member of the team, you'll collaborate closely with data scientists, software engineers, and product managers to enhance the reliability and performance of our data systems, while ...

Cogeco

Specialist, Data Engineering

Montreal, QC · On-site

Reporting to the Lead Data Engineering, the Data Engineering Specialist is responsible for ... Utilize Collibra or similar platforms to manage data catalogs, business glossaries, and data ...

Medfar

Senior Data Transfer Developer

Montreal, QC · On-site +1

... management solution for clinics, which replaces inefficient processes with a faster and safer ... As a Senior Data Transfer Developer, you will design, build, and evolve robust data transfer ...

The CSL Group Inc

Data Analyst

Montreal, QC · Hybrid

Capability to collaborate across departments and with data engineers * Skill in managing multiple tasks in a dynamic setting Knowledge of English is neces sary for this role due to daily interactions ...

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Data Engineer Manager information

What does a Data Engineer Manager do?

A Data Engineer Manager leads a team of data engineers to design, build, and maintain data pipelines and infrastructure. They collaborate with data scientists, analysts, and business stakeholders to ensure efficient data processing and accessibility. Their responsibilities include project management, team leadership, system architecture decisions, and optimizing data workflows. Additionally, they enforce best practices for data governance, security, and scalability.

What are the key skills and qualifications needed to thrive in the Data Engineer Manager position, and why are they important?

To thrive as a Data Engineer Manager, you need robust experience in data architecture, pipeline design, team leadership, and a relevant degree in computer science or a related field. Proficiency with cloud platforms (like AWS or Azure), big data tools (such as Hadoop, Spark), and certifications in data engineering or project management are highly valued. Strong soft skills like effective communication, problem-solving, and mentorship set exceptional managers apart. These competencies enable strategic oversight of technical teams and ensure reliable, scalable data solutions that meet business objectives.

What are some typical challenges a Data Engineer Manager faces in their role?

Data Engineer Managers often face the challenge of balancing technical project delivery with team development and stakeholder management. They must ensure data systems remain scalable and reliable while adapting to evolving business requirements and new technologies. Additionally, managing cross-functional communication between data engineers, analysts, and business leaders can require strong organizational and interpersonal skills. Success in this role requires staying current with industry trends and fostering a collaborative, innovative team culture.
More about Data Engineer Manager jobs
What are the most commonly searched types of Data Engineer jobs in Quebec? The most popular types of Data Engineer jobs in Quebec are:
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What job categories do people searching Data Engineer Manager jobs in Quebec look for? The top searched job categories for Data Engineer Manager jobs in Quebec are:
What cities in Quebec are hiring for Data Engineer Manager jobs? Cities in Quebec with the most Data Engineer Manager job openings:
Data Engineer Manager jobs near you
Infographic showing various Data Engineer Manager job openings in Quebec as of May 2026, with employment types broken down into 94% Full Time, 3% Part Time, 1% Temporary, and 2% Contract. Highlights an 68% Physical, 4% Hybrid, and 28% Remote job distribution.

Senior AI Data Engineer- Agentic Healthcare Platform

Medeloop

Montreal, QC

Full-time

Posted 1 hour ago

Job description

The Role

This is a full-ownership data engineering role at the center of Medeloop's AI platform. You won't be maintaining pipelines someone else built, you'll be architecting the data backbone that powers AI agents doing real operations at scale. You'll work directly with data scientists, AI engineers, and product teams to turn raw, complex healthcare data into the clean, structured, semantically-rich foundation our AI scientists depend on. Your work shows up in customer products and research outcomes, not internal dashboards that no one reads.Candidates who currently perform these tasks exclusively through manual processes are unlikely to be suitable for this role. We require an individual who has already adopted and integrated AI techniques to enhance operational velocity, rather than one who is contemplating future experimentation.If you want to build something that genuinely changes how medical research gets done, this is the role.

What You'll Own
  • The healthcare data lake: curating, extending, and evolving it through new concepts, derived variables, and data models that directly inform our AI engines and customer products
  • AI-native data workflows: designing and operating AI-powered pipelines (using tools like Claude Code and agent frameworks) to automate harmonization, cleaning, quality checks, and summarization at scale
  • NLP and semantic infrastructure: building pipelines for entity extraction, concept normalization, embedding-based retrieval, and semantic search that power the AI Scientist platform
  • Novel data extraction approaches: experimenting with and building new methodologies for working with unstructured clinical data, not just applying existing playbooks
  • Research-grade data products: delivering analytical samples, cohorts, and final datasets that withstand scientific scrutiny and are actively used by researchers and customers
  • Data governance and observability protocols: including access controls, PHI/PII handling, data classification, compliance, monitoring, alerting, data freshness, and comprehensive documentation to enable self-service capabilities.
What We're Looking For
  • 3+ years of relevant data engineering or data management within an analytics-driven organization, with end-to-end ownership from raw ingestion to final data product
  • Deep hands-on experience with healthcare CDMs (OMOP, FHIR, PCORnet) — designing or extending them, not just querying
  • Knowledge of medical ontologies: UMLS, SNOMED CT, RxNorm
  • Experience with big data, data pipelines and tooling that support retrieval-augmented generation (RAG), vector integrations, embedding workflows, and other AI/ML workloads. Experience in big data tooling such as Spark, Iceberg, EMR
  • Fluent in Python and SQL; comfortable across structured and unstructured data
  • Proven NLP experience: semantic search, entity recognition, concept normalization, embedding pipelines
  • Strong grasp of inferential statistics and cohort methodology to be a real partner to data scientists and customers (as part of onboarding)
  • Experience contributing to an AI/ML product, especially in automated research or scientific discovery
  • Experience mentoring other engineers and providing technical leadership
Bonus Points
  • Multi-cloud experience (AWS, Azure, GCP)
  • Authorship or contribution to peer-reviewed publications or technical reports
Why Medeloop
  • Ownership from day one: small team, high-trust, no layers between your work and its impact
  • Technically ambitious: you'll build AI-powered workflows, not just support them
  • Real-world stakes: your work accelerates drug development, addresses health equity, and improves clinical research for institutions that matter
  • Strong foundation: Series A, top-tier investors, and a data asset (200M+ patient records) that most companies spend years trying to build