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Data Engineer Manager Jobs in Quebec (NOW HIRING)

Ensure data quality through testing, validation, and anomaly management. * Document transformations ... A BI Developer role focused primarily on report and dashboard production. * This is a role at the ...

Ensure data quality through testing, validation, and anomaly management. * Document transformations ... A BI Developer role focused primarily on report and dashboard production. * This is a role at the ...

Ensure data quality through testing, validation, and anomaly management. * Document transformations ... A BI Developer role focused primarily on report and dashboard production. * This is a role at the ...

Ability to configure, use, and develop data management systems. * Ability to develop large-scale, structured software using software engineering best practices. * Ability to use various tools and ...

Manage and coach the individual Chapter Area Leads and Team Leads for Data Science, Data Engineering, Data Architecture, and Data Analytics, guiding them to balance operational output with functional ...

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 ...

Reporting to the Senior Software Developer, the incumbent will provide leadership in the design, governance, and optimization of data management frameworks, standards, and operational workflows that ...

Reporting to the Senior Software Developer, the incumbent will provide leadership in the design, governance, and optimization of data management frameworks, standards, and operational workflows that ...

... 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 ...

Act as the reference for product master data topics across Sustaining Engineering and Operations ... Work with R&D, Product Management, and Operations to support the creation of new items across ...

Act as the reference for product master data topics across Sustaining Engineering and Operations ... Work with R&D, Product Management, and Operations to support the creation of new items across ...

Promote DataOps, DevOps, CI/CD, and MLOps practices, including automated testing, deployment ... Strong leadership, communication, stakeholder management, strategic thinking, and influencing ...

As part of G+D's global AI transformation, the Senior Data Scientist will collaborate closely with AI Engineers, ML Engineers, Data Engineers, product and project managers, and executive stakeholders ...

Showing results 41-60

Data Engineer Manager information

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.

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

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 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 most commonly searched types of Data Engineer jobs in Quebec? The most popular types of Data Engineer jobs in Quebec are:
What are popular job titles related to Data Engineer Manager jobs in Quebec? For Data Engineer Manager jobs in Quebec, the most frequently searched job titles are:
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:
Infographic showing various Data Engineer Manager job openings in Quebec as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Senior ML Data Processing Developer

LawZero

Montreal, QC

Full-time

Medical, Retirement, PTO

Re-posted 5 days ago


Job description

We are seeking a Senior ML Data Processing Developer to participate in the development, curation, and scaling of our core data asset pipeline. Sitting at the intersection of data engineering, data curation, and machine learning, you will own the end-to-end pipeline that transforms raw web-scale data into high-signal datasets used to train the Scientist AI.

In this role, you will not just manage data; you will engineer its quality. You will design algorithmic filtering, build model-based scoring mechanics, and ensure rigorous benchmark integrity to power the next generation of AI. And as our models push beyond established paradigms, you will design and implement novel data transformations that don't yet have playbooks, working at the frontier of what training data can be.

We are hiring multiple people for this role, and responsibilities may be distributed across the team based on individual experience, skills, and interests.

Key Responsibilities
  • Partner with the Research team to define, build, automate, scale, and manage data pipelines that transform raw web-scale data into training datasets for the Scientist AI.
  • Build and maintain data processing pipelines, including deduplication, model-based quality scoring, heuristic filtering, toxicity removal, PII scrubbing, metadata extraction, and proprietary data transformations, with full dataset versioning and provenance tracking, optimizing for throughput and cost at scale. 
  • Ensure all ingested data meets compliance requirements, internal Data Governance policies, and legal obligations.
  • Develop and refine the scoring and filtering toolchain: heuristics, LLM-as-a-judge evaluators, ML classifiers, metadata extraction modules, and human-in-the-loop review workflows required for data processing and quality assurance.
  • Instrument data processing pipelines with data-quality monitoring, guardrails, and alerting to catch regressions before they propagate downstream.
  • Collaborate with the Research team and other teams to understand evolving data requirements, then identify and acquire large-scale text corpora that meet those requirements. This includes conducting systematic coverage analyses to identify gaps in the corpus and develop targeted acquisition strategies to address them, and working with the Legal & Governance Team to license new data sources.
  • Design and maintain strict leakage detection mechanisms to guard against evaluation contamination across all stages of the data processing pipeline.
  • Build internal tooling and interfaces that let researchers explore, query, and understand available datasets with minimal friction.
Skills and Qualifications
  • Degree in computer science, software engineering, or a related field.
  • Proven track record of handling massive unstructured text datasets (trillion-token scale), with 5+ years of experience in data processing, machine learning engineering or Natural Language Processing (NLP).
  • Hands-on experience with distributed processing frameworks (e.g., Spark, Ray, Flink), designing and optimizing high-throughput pipelines.
  • Experience with data privacy implementation (PII scrubbing), content-safety filtering (toxicity, bias), and evaluation-contamination prevention.
  • Demonstrated ability to work across Research, Engineering, and/or Legal/Governance teams, translating varied requirements into concrete pipeline work.
  • Strong Python proficiency, including experience writing production-grade data-processing code.
  • Experience with pipeline orchestration frameworks (e.g., Airflow, Prefect, Dagster).

Nice to have 

  • Experience training, fine-tuning, or deploying ML models for data-quality tasks (classifiers, LLM-based evaluators) and familiarity with LLM inference optimization (e.g. vLLM, SGLang).
  • Familiarity with containerized deployment (Docker, Kubernetes) and infrastructure-as-code practices.
  • Familiarity with ML experiment tracking tools (e.g. Weights and Biases).
  • Experience with data licensing workflows or web-scale data acquisition.
  • Contributions to open-source data processing or NLP tooling.
What we offer
  • The chance to contribute meaningfully to a globally critical initiative
  • Comprehensive health benefits (including mental health and wellness management account)
  • 20 days of vacation per year upon start
  • Employer contribution of 4% to your retirement savings, with no required employee match
  • Additional compensation totaling 8% of your salary to apply towards additional retirement savings or bonuses (independent of group and individual performance)
  • A team of passionate world-class experts in their field
  • A collaborative and inclusive work environment in our vibrant office space in the heart of Little Italy, in the trendy Mile-Ex district, close to public transportation