About this role

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.

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.

Full-Stack Data Platform Engineer

Key skills