Posted 8 months ago
Full-Stack Data Platform Engineer
@ Reflow
Toronto, Ontario
Overview
Reflow is hiring a full-stack data platform engineer to design and operate the data systems behind its workforce and workflow intelligence platform. The role covers warehouse architecture, ETL pipelines, dataset modeling and dashboards. The posting offers full-time or part-time work with pay set by market and location, and gives no pay range.
Responsibilities:
- Design and maintain a scalable data warehouse
- Develop and optimize ETL pipelines from APIs and internal systems
- Model and manage datasets for analytics and product features
- Build dashboards and visualization tools
- Implement event-based pipelines for real-time analytics
Requirements summary:
- Experience with data warehouse architecture and analytics infrastructure
- Strong SQL, data modeling and pipeline performance skills
- Hands-on experience with ETL tools and cloud-based data operations
- Python for analytics is a bonus
- Understanding of data governance and secure cloud operations is a bonus
Tools & skills
Source and dates
Employer career site / ATS feed · ashby
- Employer posting date
- 2026-03-18
- First seen by our source
- 2026-10-08
- Source record updated
- 2026-10-09
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Department | Data & analytics |
| Hours per week | 40 (estimated) |
| Work setting | Home |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Reflow
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Get real-time visibility, make data-driven decisions, and measure ROI from automation and optimization.
Full company description
Reflow gives operations teams real-time visibility into how work actually flows, so they can identify what to optimize and automate what matters. It shows leaders where work slows down across teams and systems and what's driving cost and friction. Teams can get up and running in a day and start seeing where work breaks or drifts, without a heavy setup process. From there, Reflow surfaces the highest-impact opportunities for optimization and automation, so prioritization isn't guesswork. As changes roll out, teams can track whether they reduced cost, improved speed and quality, or lowered risk, and measure ROI over time.
- LinkedIn followers
- 635
- People associated on LinkedIn
- 16
- Reported office locations
- San Francisco, Ca, US
- Business categories
- Software
- Enterprise Applications
- B2B
- Customer Service
- Other recorded names
- Reflow
- Profile identifies a recruitment agency
- No
- Reported total investment
- 15,000,000
Currency and observation date were not supplied; this is not a current valuation or a funding round.
Reflow gives operations teams real-time visibility into how work actually flows, so they can identify what to optimize and automate what matters. It shows leaders where work slows down across teams and systems and what's driving cost and friction. Teams can get up and running in a day and start seeing where work breaks or drifts, without a heavy setup process. From there, Reflow surfaces the highest-impact…
| Field | Value |
|---|---|
| Industry | Technology, Information and Internet |
| Company size | 11-50 employees |
| Headquarters | San Francisco, Ca |
| Organization type | Privately Held |
| Year founded | 2024 |
| Open jobs on Jobsy | 7 |
| View page |
We’re building Reflow, a workforce and workflow intelligence platform that helps teams deeply understand how work gets done. As we scale, the data we collect is becoming richer and more complex. We need a data platform engineer to help us design and operate the systems that turn that data into intelligence — powering analytics, workflow insights, and economic modeling.
What you’ll do
Design, implement, and maintain a scalable data warehouse (BigQuery, Snowflake, Redshift, or similar).
Develop and optimize ETL pipelines to ingest data from APIs and internal systems.
Model and manage datasets to support flexible analytics and product features.
Collaborate with engineering team to improve data mining and analytics performance.
Build and maintain dashboards and visualization tools (Metabase, Tableau, Power BI) to enable internal and external insights.
Ensure data reliability, cost efficiency, and performance optimization across environments.
Implement event-based pipelines for real-time analytics and reporting.
Contribute to data governance, privacy, and security best practices.
Who you are
Experienced in data warehouse architecture and scalable analytics infrastructure.
Strong with SQL, data modeling, and pipeline performance optimization.
Hands-on with ETL tools, data ingestion frameworks, and cloud-based data operations.
Capable of balancing technical depth with real-world impact — you build systems people actually use.
Comfortable navigating tradeoffs between cost, scalability, and complexity.
Curious about how data translates into insights, decisions, and automation.
Bonus points
Experience with Python for analytics and data wrangling.
Familiarity with AI/ML-driven analytics or predictive modeling.
Exposure to real-time or streaming data architectures.
Understanding of data governance, compliance, and secure cloud operations.
Why join
You’ll build the backbone of Reflow’s intelligence layer, the systems that make our data usable, fast, and insightful. You’ll work directly with founders and engineers across analytics, infrastructure, and product. This is a high-impact technical role that sits at the intersection of scale, performance, and strategy.
We’re open to part or full-time. Ideal for builders who care about performance and precision at scale.
Compensation:
We offer competitive pay based on the market and where you’re located. The salary ranges in our job postings are intentionally wide because they need to cover both U.S. and international candidates. Our final offer will depend on things like your experience, skill set, and location.
Journal
Only you can see this. Kept on this device, and in your account when you sign in.