Full-Stack Data Platform Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 206d ago
The date the source published, not the day we noticed it (2026-03-18). Last seen at its source just now.
We have tracked this listing since 5 Oct 2026 (5 days). The employer's own board has carried it every time we have read it, most recently just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Canada, LATAM, Europe
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay CA$140k–195.4k/yr
Middle 50% of 314 listings that do state pay — Engineering · all levels · Canada · CAD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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Ashby employer's own board first seen 5d ago · last seen just now
The listing
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.