DR We need someone who can turn millions of messy transactions into clean, fast, "aha moment ... SQL fluency -- complex transformations, window functions, performance tuning * ETL/ELT chops -- you ...
DR We need someone who can turn millions of messy transactions into clean, fast, "aha moment ... SQL fluency -- complex transformations, window functions, performance tuning * ETL/ELT chops -- you ...
Remote Window Cleaner information
How much do window washers get paid hourly?
Hourly wages for window washers typically range from $12 to $25, depending on experience, location, and whether they work for a company or independently. Skilled window washers with specialized equipment or certifications may earn higher rates, especially for high-rise or commercial projects.
What is the difference between Remote Window Cleaner vs On-site Window Cleaner?
| Aspect | Remote Window Cleaner | On-site Window Cleaner |
|---|---|---|
| Credentials | Minimal; often requires basic cleaning certifications or experience | Same as remote; may need local licensing or certifications |
| Work Environment | Remote; primarily virtual coordination, scheduling, and customer communication | Physical; cleaning windows at client locations |
| Employer & Industry Usage | Used by cleaning companies offering remote consultation or management | Traditional window cleaning services at physical sites |
| Search & Comparison Intent | People comparing remote cleaning jobs or virtual roles | People seeking physical window cleaning jobs |
Remote Window Cleaners typically handle scheduling, customer support, and consultation remotely, while On-site Window Cleaners perform the actual cleaning at physical locations. Both roles may require similar certifications, but their work environments differ significantly, with remote roles focusing on virtual tasks and on-site roles involving physical labor.
What are the key skills and qualifications needed to thrive as a Remote Window Cleaner, and why are they important?
To thrive as a Remote Window Cleaner, you need strong attention to detail, manual dexterity, and experience with commercial or residential cleaning, often supported by a valid driver's license and basic safety training. Familiarity with window cleaning tools such as water-fed poles, squeegees, extension ladders, and sometimes the use of specialized equipment or cleaning solutions is typical. Excellent customer service, reliability, and time management are key soft skills to build client trust and ensure efficient job completion. These skills and qualities are crucial for delivering high-quality results, maintaining safety standards, and fostering repeat business in a competitive cleaning industry.
Is window cleaning a good side hustle?
Window cleaning is a common side hustle that can provide flexible income, especially for those with basic cleaning skills and access to tools like squeegees and ladders. It often requires minimal startup costs and can be scheduled around other commitments, making it suitable for part-time work. However, physical effort and safety precautions are important considerations for success in this role.
What are remote window cleaners?
Remote window cleaners are professionals who clean windows on buildings, homes, or commercial properties without being physically present at the location. They typically use specialized equipment, such as robotic window cleaning devices or remotely operated machinery, to perform the cleaning tasks from a distance. This approach enhances safety by reducing the need for workers to be on scaffolding or ladders, especially on high-rise buildings. Remote window cleaning can also improve efficiency and reach difficult or hazardous areas that would be challenging for traditional cleaners.
How much do window cleaners get paid per house?
Window cleaners typically earn between $10 and $25 per house, depending on the size, complexity, and location of the job. Experienced cleaners or those working in high-cost areas may charge higher rates, and some may work on an hourly basis instead of per house.
Do robot window cleaners do a good job?
Robot window cleaners can effectively clean smooth glass surfaces and are useful for routine maintenance, especially in hard-to-reach areas. However, they may not perform as well on textured or heavily soiled windows and often require manual oversight or additional cleaning for optimal results.
What are some common challenges remote window cleaners face, and how can they be addressed?
Remote window cleaners often encounter challenges such as coordinating schedules with clients, ensuring access to buildings, and managing safety protocols without direct on-site supervision. To address these, clear communication with clients and property managers is crucial, as is using digital tools for scheduling and progress tracking. Additionally, staying updated with safety training and remote monitoring technologies can help ensure jobs are completed efficiently and safely.
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Full-time
Re-posted 17 days ago
Job description
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.
Employment Type: FULL_TIME