The TL;DR

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."

What's the actual job?

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:

• Building ETL/ELT pipelines that ingest, transform, and serve data at scale
• Designing warehouse schemas (star schemas, fact tables, the whole dimensional modeling thing)
• Creating pre-aggregated datasets so dashboards load fast and analysts stay happy
• Making sure data flows reliably from source systems → transformations → analytics layer

Some of your time:

• Partnering with analytics team to understand what data they actually need
• Optimizing the infrastructure so it doesn't cost a fortune or fall over
• Building data quality checks because garbage in = garbage out

Salary: 120-150K CAD

Our hot take on AI

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.

You should have

• 5+ years in data engineering (not just DBA work — actual pipeline and warehouse experience)
• SQL fluency — complex transformations, window functions, performance tuning
• ETL/ELT chops — you've built pipelines that process serious volume
• Data modeling experience — star schemas, SCDs, fact vs dimension tables
• Python or C# — for the stuff SQL can't do
• Cloud experience — Azure preferred (Data Factory, Azure SQL, Functions)

Bonus points for

• SaaS or multi-tenant analytics experience
• Restaurant/retail/loyalty domain knowledge
• Real-time or near-real-time data pipeline experience
• Having opinions about dbt, Airflow, or modern data stack tools

The vibe check

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

Tech stack

SQL Server, PostgreSQL, Clickhouse, Azure (Data Factory, Functions, DevOps), C#, Python, Redis.

What We Offer

• Generous time off plan
• Fully remote work & support to assist with making your remote office space as comfortable as possible!
• Continuous virtual coaching and support
• Comprehensive health benefits
• Subsidized gym membership
• Performance recognition
• Professional development program
• Growth opportunities (we really mean it!)

About TapMango

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.