Full-Stack Data Platform Engineer

About the role

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 design and operate the systems that turn that data into intelligence, powering analytics, workflow insights, and economic modeling.

Key responsibilities

• 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 the engineering team to improve data mining and analytics performance.
• Build and maintain dashboards and visualization tools (Metabase, Tableau, 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.

Required profile

• 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.
• Comfortable navigating trade‑offs between cost, scalability, and complexity.
• Curious about how data translates into insights, decisions, and automation.

Required skills

• BigQuery
• Snowflake
• Redshift
• SQL
• ETL tools
• Data ingestion frameworks
• Metabase
• Tableau
• Power BI
• Python
• AI/ML‑driven analytics
• Real‑time streaming data architectures