Data Platform Engineer II

Vancouver, Greater Vancouver

On-site

Full-time

$90K – $120K CAD

2 weeks ago

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Employment type: Full-time · On-site
Posted: September 22, 2026
Salary range: $90,000–$120,000 CAD per year
Province: British Columbia (BC)

Hiring confidence: Some gaps · 56/100

Some signals are missing from this posting. It may well be genuine, but it is worth confirming the role is still open before you invest time in applying. How this is scored

Job Overview

Jobs

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Job Description Job Description About us: Spring Financial is a Canadian financial technology company focused on making every day financial services simpler, faster, and more accessible . We build technology that helps Canadians build credit, save money, and access lending products without unnecessary friction. Our platforms allow customers to apply and manage their finances online, by text, or over the phone , making the experience convenient and flexible. Since launching in 2014, Spring has g…

This role is based in British Columbia. Spring Financial Inc. is hiring for this full-time position through Jobily, where you can check how well your resume matches the posting before you apply.

Market context

About this role in British Columbia

Average salary for Data Platform Engineer II in British Columbia

We do not have a salary benchmark for this title in British Columbia yet. The posting advertises $90,000–$120,000.

NOC code

This posting has not been matched to a NOC 2021 unit group yet. Use the NOC finder to identify the code from the duties listed above.

Typical qualifications for Canadian employers

2-4 years of data engineering experience
Proficiency in SQL and Python
Experience with cloud platforms (AWS, GCP, or Azure)
Understanding of ETL/ELT processes
Knowledge of data warehousing concepts

Fit check

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What you'll do

Design and build scalable data pipelines
Develop and maintain ETL/ELT processes
Optimize data warehouse performance
Collaborate with data analysts and scientists
Monitor and troubleshoot data infrastructure
Document data architecture and processes
Implement data quality checks and validation

What you'll need

2-4 years of data engineering experience
Proficiency in SQL and Python
Experience with cloud platforms (AWS, GCP, or Azure)
Understanding of ETL/ELT processes
Knowledge of data warehousing concepts
Experience with distributed data processing tools