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A data-focused SaaS company in Canada seeks a Data Engineer to develop robust ETL pipelines, transform chaotic data into insights, and design effective data warehouse schemas. The role requires 5+ years of data engineering experience, SQL fluency, and cloud expertise, particularly in Azure. Employees benefit from remote work, generous time off, and comprehensive health packages amidst a dynamic team environment focused on real analytics.
We need someone who can turn millions of messy transactions into clean, fast, "aha moment" analytics for thousands of merchants.
You'll build the data pipelines that power dashboards, design the warehouse schemas that make queries actually usable, and own the infrastructure that turns "we have data" into "we have insights."
You're the bridge between raw operational chaos and polished analytics. Every time a merchant checks their performance dashboard, your pipelines are what made that possible.
Most of your time:
Some of your time:
Salary: 120-150K CAD
We use AI tools. A lot. Claude, Cursor, Copilot — the whole squad.
If you're spending 20 minutes writing boilerplate transformation logic that an AI could generate in 20 seconds, we're going to have a conversation. Your brain is expensive. Use it for pipeline architecture, data modeling decisions, and catching when the AI's output would quietly corrupt your downstream tables.
We want engineers who use AI like a power tool — to build faster, not to think for them.
Month 1: Understanding our data sources, shipping pipeline improvements, getting friendly with the analytics team
Month 2: Owning end-to-end data flows, building monitoring that catches issues before anyone notices
Month 3: Designing new analytics infrastructure, setting standards, helping others level up
SQL Server, PostgreSQL, Clickhouse, Azure (Data Factory, Functions, DevOps), C#, Python, Redis.
We're a SaaS company helping businesses run loyalty programs and online ordering. The data powers merchant-facing analytics — real insights, not vanity metrics. Small team, interesting problems, zero synergy-alignment meetings.
Interested? Tell us about a data pipeline you built that you're proud of bonus if it involved taming chaotic source data.
Disclaimer: We use AI-assisted tools to support application screening. Final hiring decisions are made by our human hiring team.
TapMango welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.
This is a newly created role, and responsibilities may evolve over time.