Software Engineer, Growth Data Platform

Responsibilities

• Build and scale the data platform that turns messy GTM signals into reliable, auditable workflows
• Design queues, and workers for enrichment, routing, assignment, and activation
• Integrate external data sources and APIs across CRM, sales engagement, ads, first and third party intent, and enrichment vendors
• Work directly with various GTM teams to turn one-off experiments into reusable platform primitives
• Debug production issues across Snowflake, dbt, Dagster, AWS, vendor APIs, webhooks, and downstream business systems

About You

• 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

Tech Stack

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
• Fivetran
• Python and SQL
• Terraform and GitHub Actions
• Soda
• Omni

Location

This role allows for a hybrid schedule in our SF headquarters. If you are based anywhere else in the US, the role is remote.