Data Engineer

DATA ENGINEER / BACKEND ENGINEER (DATA PLATFORM & INTEGRATIONS)

We’re looking for a Data Engineer / Backend Engineer to take ownership of how data flows from our data science systems into our customer-facing product.

Today, our data lives across Microsoft Azure, Databricks, microservices, and Supabase. While each part works well in isolation, the connections between them are too manual, fragile, and inefficient. Your role will be to design and build the systems that make this seamless, reliable, and scalable.

You’ll join a small, ambitious product team of 8 engineers and work closely with both backend developers and data scientists to bridge the gap between experimentation and production.

• Own the architecture and implementation of data pipelines between Databricks, Azure, and our application stack
• Design and build robust data flows into Supabase (Postgres) for product use
• Replace ad hoc scripts and manual processes with reliable, observable systems
• Build and maintain microservices that expose data to the product in a clean and scalable way
• Set up and manage scheduled jobs (cron, event-driven pipelines, etc.)
• Collaborate with data scientists to productionize models and datasets
• Improve data quality, consistency, and performance across systems
• Help define best practices for how we structure and move data across the company

• Strong experience with Postgres and SQL (data modeling, performance tuning, migrations)
• Solid backend experience (TypeScript and/or Python)
• Experience with data platforms like Databricks and cloud environments (Azure preferred)
• Experience building APIs or microservices for data access
• Familiarity with Supabase or similar Postgres-based platforms is a plus
• Experience with scheduling, orchestration, or workflow tools (e.g. cron, Airflow, or similar)
• Ability to think in systems and architecture, not just individual scripts
• Comfortable taking ownership and driving technical decisions

• Experience working closely with data science teams
• Understanding of analytics pipelines, feature stores, or ML workflows
• Experience improving or standardizing messy data flows in growing teams

• A high-impact role with real ownership over a critical part of our platform
• A small, experienced, and fast-moving engineering team
• The opportunity to shape how data flows across the entire product
• A pragmatic engineering culture focused on shipping and improving