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Compass, a Kicksaw Company

Data Engineer

Montreal, QC, Canada

Full-time

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Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Oct 29, 2026
Posting language: English
Posted: May 15, 2026

Original job description

Role Description

Compass Analytics is excited to recruit a talented and driven Data Engineer to join our growing Analytics Delivery team. The ideal candidate will have a passion for building data solutions, including pipeline development, implementing DataOps best practices, and collaborating with stakeholders.

About Compass Analytics

Compass Analytics specializes in delivering end-to-end data solutions to clients across diverse industries ranging from Aviation, Healthcare, Financial Services, Retail, and Sports. Our expertise spans across multiple disciplined including Data Architecture, Data Engineering, Data Governance, Artificial Intelligence & Machine Learning, Process Automation, and Dashboarding. We pride ourselves on fostering a culture that emphasizes purpose in what we are building for our clients, elegance and rigor in how we work with everyone, and a fun environment as we get work done.

Based in Montréal, Québec, Compass Analytics is composed of talented data professionals who support their clients in their data transformation initiatives. Our clients lean on us to bring their data ideas into reality.

Role Details

Position: Data Engineer
Number of Open Roles: One (1)
Location: Montreal, QC (Hybrid)
Duration: Permanent Full-Time

Key Responsibilities

Under the guidance of our Leadership Team & Project Managers, the Data Engineer will be responsible for the following tasks:

Collaborate with stakeholders to design and implement scalable and efficient data architecture, including table structures, lineage, and data flow across layers.
Conduct data audits on source systems to document and address potential quality issues.
Build and maintain data ingestion and transformation pipelines to ensure reliable and timely data delivery.
Develop and implement production-ready pipelines with a focus on DataOps best practices for monitoring, orchestration, and automation.
Establish and implement data governance standards, ensuring data availability, usability, integrity, and security.
Create and maintain comprehensive technical documentation for all completed work.
Support AI and Machine Learning projects as well as other projects within the scope of the assigned mandate (e.g., dashboarding or automation).

Technical Capabilities

Programming Languages: Proficiency in SQL and Python is essential; experience with Scala, Spark, or other languages is a plus.
Platforms: Knowledge of platforms suchs as Databricks, Snowflake, AWS, Azure, or Google Cloud.
DataOps: Familiarity with CI/CD pipelines and tools such as GitHub for version control and deployment.
Collaboration Tools: Experience with JIRA and Confluence is a plus.

Minimum Requirements

Education: Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or a related field.

Preferred Qualifications

Problem Solving: Strong analytical and problem-solving skills with the ability to troubleshoot complex data issues.
Organized & Rigorous Approach: Strong organizational skills and attention to detail, ensuring rigor in development and accuracy in outputs.
Communication: Excellent verbal and written communication skills, with the ability to collaborate effectively across teams.

How To Apply

APPLICATION PORTAL

If you’re excited about leveraging your skills to create impactful data solutions, we’d love to hear from you! Please submit your resume, cover letter, along with any other portfolio assets through our website’s careers section.

Application URL: https://www.compassdata.ca/careers

Step 2: LEADERSHIP INTERVIEWS – 2 ROUNDS

Selected candidates will be invited to interview (read: have a conversation) with William Chan, Scott Carr, or Pentcho Tchomakov. The interview will last between 30-60 minutes. You will be asked to present your experiences and previous work deliverables/projects. The interview is an opportunity for us to get to know each other better!

Step 2a: TECHNICAL INTERVIEW

Selected candidates will be re-invited for a technical interview in form of a take home case. Candidates will have several days to complete the technical case and present it to a small panel in the form of an open Q&A conversation.

Step 3: FORMAL OFFER

The selected candidate will receive a verbal and written offer (via email). Once accepted and signed, you will begin the new employee onboarding process!

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More about this job

Responsibilities

Design scalable data architectures, audit source data, and build and maintain reliable ingestion and transformation pipelines. Apply DataOps and governance practices, document technical work, and support AI/ML, dashboarding, and automation projects.

Requirements

A bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or a related field is required, along with proficiency in SQL and Python. The role also calls for analytical problem-solving, strong organization and attention to detail, and effective written and verbal communication; experience with cloud platforms and CI/CD tools is relevant.

Skills

SQL
Python
Data Architecture
Data Engineering
Data Pipeline Development
Data Ingestion
Data Transformation
DataOps
CI/CD
Data Governance
Data Quality
Data Lineage
Databricks
Snowflake
Cloud Platforms
Technical Documentation

Visa sponsorship

Not detected in the job text

Hiring contact

William Chan

Keywords

SQL
Python
Scala
Spark
Databricks
Snowflake
AWS
Azure
Google Cloud
GitHub
JIRA
Confluence
Data Architecture
Data Engineering
Data Pipelines
Data Ingestion
Data Transformation
DataOps
CI/CD
Data Governance
Data Quality
Data Lineage
Data Flow
Data Audits
Monitoring
Orchestration
Automation
Artificial Intelligence
Machine Learning
Dashboarding

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