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Sr Data Engineer Jobs in Quebec (NOW HIRING)

We are seeking a visionary and highly technical Senior ML Data Platform Developer to architect, implement, scale, and maintain the data engine powering our next-generation frontier models. In this ...

Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts are all ...

University degree in Computer Science, Engineering, or a related field. Relevant Experience * Minimum of 5 years of industry experience in development, coding, scripting, and data-oriented design.

Within the Data Lab, you will work in a modern data ecosystem with multidisciplinary teams (data science, analytics, engineering, product) on high-impact end-to-end use cases (anomaly detection ...

... Consulting Senior Data Architect with deep, production\-grade Microsoft Fabric experience to ... Architect and implement Fabric solutions for data engineering (Spark), Data Factory pipelines , and ...

Overview of the Role The Data & Analytics Crew Lead (Senior Director) occupies a hybrid leadership ... Data Science, Data Engineering, Data Architecture, and Data Analytics . You are simultaneously the ...

We are looking for a senior Data Analyst that can be not only an employee of a great team but also ... Work with engineers to create data tracking framework * Provide data visualization using specified ...

Showing results 41-60

Sr Data Engineer information

What is the difference between Sr Data Engineer vs Data Engineer?

AspectSr Data EngineerData Engineer
Required CredentialsBachelor's degree in CS or related field; 3+ years experience; SQL, Python, SparkBachelor's degree in CS or related field; 1-3 years experience; SQL, Python, Spark
Work EnvironmentCollaborates with data scientists, analysts; designs scalable data pipelinesBuilds and maintains data pipelines; supports data analysis
Employer & Industry UsageTech companies, finance, healthcare; used for complex data projectsStartups, enterprises; used for data collection and processing

The main difference between a Sr Data Engineer and a Data Engineer lies in experience level, responsibilities, and complexity of projects. Sr Data Engineers typically have more experience, handle more complex data architecture, and mentor junior staff, whereas Data Engineers focus on building and maintaining data pipelines. Both roles are essential in data-driven organizations, but the senior role involves greater technical leadership and strategic planning.

What are the key skills and qualifications needed to thrive as a Sr data engineer, and why are they important?

To thrive as a Sr Data Engineer, you need expertise in data architecture, ETL processes, programming (such as Python or Scala), and a strong background in computer science or a related field. Familiarity with big data technologies like Hadoop, Spark, cloud platforms (AWS, Azure, GCP), and database management systems, along with relevant certifications, is typically required. Advanced problem-solving abilities, attention to detail, and strong collaboration skills help set top performers apart in this role. These skills and qualities ensure the efficient design, implementation, and maintenance of robust data pipelines that enable data-driven decision-making across the organization.

How do Sr data engineers typically collaborate with data scientists and analysts within a project team?

Sr Data Engineers play a crucial role in bridging the gap between raw data and actionable insights. They work closely with data scientists and analysts to understand data requirements, design robust data pipelines, and ensure the reliability and scalability of data infrastructure. Regular collaboration involves translating analytical needs into technical specifications, optimizing data flow, and troubleshooting data issues. This teamwork ensures that data-driven projects progress smoothly and that the analytical team has timely access to clean, well-structured data.

What is a Sr data engineer?

Sr Data Engineers, or Senior Data Engineers, are experienced professionals responsible for designing, building, and maintaining scalable data pipelines and architectures. They work with large datasets, ensuring data quality, reliability, and accessibility for analytics and business intelligence purposes. Sr Data Engineers collaborate with data scientists, analysts, and other stakeholders to implement data solutions that support decision-making and business growth. Their expertise often includes proficiency in programming languages like Python or Java, experience with big data tools such as Hadoop or Spark, and a deep understanding of database systems.
What are popular job titles related to Sr Data Engineer jobs in Quebec? For Sr Data Engineer jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Sr Data Engineer jobs in Quebec look for? The top searched job categories for Sr Data Engineer jobs in Quebec are:
What cities in Quebec are hiring for Sr Data Engineer jobs? Cities in Quebec with the most Sr Data Engineer job openings:
Infographic showing various Sr Data Engineer job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% 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