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!
