Architect, build, and maintain scalable data pipelines and ETL processes.
Improve data warehouse performance and implement data quality frameworks.
Collaborate with Product, Engineering, and GTM to translate requirements into data solutions.
Develop automated monitoring to proactively identify pipeline bottlenecks.
Execute high-priority ad-hoc data requests to support stakeholder decisions.

🎯 Requirements

7+ years in data engineering roles, preferably in high-growth settings.
Advanced data modeling and warehouse design (Star/Snowflake) and ETL/ELT.
Snowflake, Airflow, dbt and the modern data stack.
AWS-based cloud infrastructure and distributed systems management.
Stream processing with Kafka or Kinesis.
Strong problem solving in ambiguity with tight deadlines.

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