Senior Data Engineer (Analytics Focus)

Toronto - Canada

Monthly Salary: Not Disclosed

Posted on: 11 hours ago

Vacancies: 1 Vacancy

Job Summary

The TL;DR

We need someone who can turn millions of messy transactions into clean fast aha moment analytics for thousands of merchants.

Youll 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.

Whats the actual job

Youre 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 doesnt 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 youre spending 20 minutes writing boilerplate transformation logic that an AI could generate in 20 seconds were going to have a conversation. Your brain is expensive. Use it for pipeline architecture data modeling decisions and catching when the AIs 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 youve built pipelines that process serious volume
Data modeling experience star schemas SCDs fact vs dimension tables
Python or C# for the stuff SQL cant 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

Were 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 youre 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.

Required Experience:

Senior IC

The TL;DRWe need someone who can turn millions of messy transactions into clean fast aha moment analytics for thousands of merchants.Youll 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 ...