Full-Stack Data Platform Engineer

🕒 March 24

🇩🇪 Germany – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 34%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Reflow

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2024

☁️ SaaS

🏢 Enterprise

🤝 B2B

SaaS • Enterprise • B2B

Reflow is a SaaS platform that provides enterprise teams real-time visibility into how operational work actually happens, helping them visualize workflows, identify bottlenecks and drift, prioritize data-driven automation, and measure ROI from optimization. Built as a system of record for enterprise operations, Reflow aggregates granular execution data across tools to surface objective insights, recommend high-impact automations (e. g. , refund processing, chargeback triage, subscription cancellations), and verify compliance with SOPs while maintaining enterprise-grade security and privacy controls.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Competitive pay based on market rates and location