Full-Stack Data Platform Engineer
$80k – $160k • 0.0% – 0.4% 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 system...
or continue with email
$80k – $160k • 0.0% – 0.4% 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 system...
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