Full-Time
Full-Stack Data Platform Engineer
Reflow
11-50 employees
Transforms operational activity into actionable insights
No salary listed
Remote in Canada + 1 more
More locations: Toronto, ON, Canada
Remote
 DevOps & Infrastructure (1) |
|---|
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- Experience in data warehouse architecture and scalable analytics infrastructure.
- Strong proficiency in SQL, data modeling, and pipeline performance optimization.
- Hands-on experience with ETL tools, data ingestion frameworks, and cloud-based data operations.
- Ability to balance technical depth with real-world impact.
- Ability to navigate tradeoffs among cost, scalability, and complexity.
- Design, implement, and maintain a scalable data warehouse using BigQuery, Snowflake, Redshift, or a similar platform.
- 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 the engineering team to improve data mining and analytics performance.
- Build and maintain dashboards and visualization tools such as Metabase, Tableau, and Power BI for 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.
- Experience with Python for analytics and data wrangling.
- Familiarity with artificial intelligence and machine-learning-driven analytics or predictive modeling.
- Exposure to real-time or streaming data architectures.
- Understanding of data governance, compliance, and secure cloud operations.
Reflow provides an enterprise-grade workforce and workflow intelligence platform that reveals how work actually happens across teams and systems, helping plan AI and automation investments. It converts operational activity into structured data and delivers real-time views of task flows, bottlenecks, and deviations without complex integrations or manual time tracking. It differentiates itself with a privacy-first design and system-level visibility (not employee monitoring) and SOC 2 Type 2 controls. The goal is to help mid-market and enterprise organizations optimize processes and achieve measurable ROI from automation, as evidenced by early customer savings.
Company Size
11-50
Company Stage
Seed
Total Funding
$15M
Headquarters
San Francisco, California
Founded
2024
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Simplify's Take
What believers are saying
- February 2026 seed funding exceeded $15 million, giving Reflow fresh runway for growth.
- Early customers reported millions in savings, including one finance leader citing $1.2 million.
- Enterprises adopting AI in 2026 need process visibility before automation, matching Reflow's pitch.
What critics are saying
- ActivTrak, Insightful, and Teramind already own adjacent employee visibility budgets in 2026.
- Employees and unions will resist hidden workflow capture, slowing deployment across 2026 renewals.
- If enterprise buyers reject trust-heavy monitoring, Reflow becomes a niche analytics tool, not infrastructure.
What makes Reflow unique
- Reflow launched in February 2026 as an operational intelligence layer, not a time tracker.
- Its privacy-first, system-level visibility maps work across people and systems without complex integrations.
- SOC 2 Type 2 and configurable metadata controls target regulated enterprise buyers directly.
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Benefits
Flexible Work Hours
Growth & Insights and Company News
6 month growth
↓ -4%1 year growth
↓ -4%2 year growth
↓ -4%We led Reflow’s $15M Seed to build the system of record for operational intelligence — bringing visibility and measurable ROI to enterprise AI automation.
Reflow launches following a $15M+ seed round focused on operational visibility for enterprises. The company plans to scale its platform to more mid-market and enterprise customers while expanding workflow and workforce intelligence capabilities to help organisations understand work processes before applying automation or AI. Reflow has closed a seed funding round of more than $15 million to support ongoing technology development and broaden access to its workflow and AI automation intelligence, alongside the launch of its workforce and workflow intelligence platform for enterprise customers. As organisations adopt AI, many are able to measure outcomes but have limited visibility into the processes that produce them. As operations scale, this can make it more difficult to assess capacity, identify automation opportunities, or evaluate the impact of AI initiatives. Reflow is designed to address this challenge by making operational work observable. The platform provides real-time visibility into how work moves across people, systems, and processes, without relying on time tracking, self-reported data, or complex integrations. By converting operational activity into structured data, it enables organisations to identify workflows suitable for automation and assess the results of those efforts. The platform takes a system-level approach, observing workflows end to end to surface task flows, bottlenecks, and process deviations. This supports more informed decisions around automation and optimisation and is suited to mid-market and enterprise organisations with large operational teams performing high-volume, computer-based work across functions such as customer support, accounting, legal, and compliance. Reflow is built to support understanding of workflows and capacity rather than monitoring individual employees. The platform incorporates privacy-focused design principles and enterprise-grade controls, including configurable metadata collection and flexible visibility settings. Founded by Ugur Kaner, a founder with Turkish roots now based in the United States, Reflow builds on prior experience in developing technology platforms for business users. Commenting on the launch and funding, Kaner said: Reflow gives leaders a clear, shared view of how work actually happens, so automation decisions are grounded in reality, not assumptions. In an AI-driven world, that visibility becomes essential infrastructure. Early users of the platform have reported improved visibility into operational capacity, more efficient resource allocation, and clearer identification of workflows suitable for automation. Looking ahead, the company plans to scale its platform to support a broader set of mid-market and enterprise customers while continuing to invest in product development. Its focus is on expanding workflow and workforce intelligence capabilities that help organisations better understand how work is performed before applying automation or AI, with the goal of establishing the platform as foundational infrastructure for AI-driven enterprise operations.