Data Engineer

Responsibilities

• Build and maintain production-ready data pipelines using DBT, Snowflake, and modern orchestration tools.
• Own data engineering features end-to-end, from implementation through optimization and deployment.
• Fix and improve existing pipelines - identify bottlenecks, resolve issues, and enhance performance.
• Drive automation initiatives across the data stack to accelerate delivery and reduce manual interventions.
• Provide 2nd line support for B2B customers - investigate data issues, clarify edge cases, and ensure customers can trust their data.
• Design and implement new data import pipelines as we expand our data source coverage.
• Implement data quality improvements - validation, monitoring, and testing to ensure reliable, accurate data delivery.
• Contribute to code reviews, architectural discussions, and data engineering best practices.

Languages

Required

• Strong fundamentals in SQL, data modeling, Python and ETL/ELT principles.
• DBT - hands-on experience building and maintaining transformation pipelines

Nice to have

• Snowflake
• Databricks
• AWS (S3, Lambda, Glue, etc.)
• Prefect or similar orchestration tools (Airflow, Dagster)
• Async-first mindset - can work independently, document decisions, and keep stakeholders informed without constant synchronous communication.