• 2+ years of experience building data platforms, backend systems, workflow engines, or data / ML infrastructure
• Deep experience with analytical data systems such as Snowflake, Databricks, BigQuery, dbt, Spark, Airflow, Dagster, or similar tools
• Track record of owning complex, end-to-end systems that serve real users or business-critical workflows
• Clear judgment about data modeling, schema evolution, contracts, lineage, and long-term maintainability
• You care whether the workflow actually works, whether customers trust it, and whether downstream teams can explain the output
• Strong debugging instincts
• You are not expected to have experience with every tool listed below, but you should be excited to work across data infrastructure, backend services, and orchestration.
• Snowflake as the warehouse and operational data store for modeled data, queues, workflow state, and activation outputs
• dbt for transformation, data models, and tests
• Dagster for orchestration of scheduled jobs, dependency-aware workflows, and operational retries
• AWS Batch and Lambda for custom workers, vendor enrichment jobs, webhook handling, and stateful background processing
• Terraform and GitHub Actions