Data Engineer

Quick Facts

• Role: Data Engineer (Data Platform)

Description

Build the data pipelines that power customer-facing features across the platform, including AI/ML, analytics, and reporting layers. Design and maintain ETL/ELT pipelines and data processing in Azure Databricks, and help set standards for data governance and data accuracy. Collaborate with the team on shared platform ownership covering Terraform/IaC, DevOps, reliability, security, and performance.

Responsibilities

• Build pipelines behind customer features across the product suite, plus AI/ML, analytics, and reporting
• Design and maintain ETL/ELT pipelines and data processing on Azure Databricks
• Contribute to platform ownership: Terraform, IaC, DevOps, reliability, security, performance
• Shape data governance patterns and ensure data remains accurate
• Help prioritize and evolve the backlog by bringing ideas and challenging assumptions
• Identify gaps in the platform and address them proactively

Requirements

• Python (PySpark) and strong SQL for large-scale datasets
• Hands-on ETL/ELT design in a lakehouse environment
• Infrastructure as code experience (Terraform) and comfort with DevOps work
• Solid data modeling and integration with discipline to keep data trustworthy

Benefits

• Real influence on how a young platform is built; your patterns will last
• Deep, hands-on Databricks experience on a stack shaping data and AI at scale
• Mission-driven work where products feel like one product due to what the team builds
• Continuous learning in a people-first culture that values curiosity