Data Engineer

Role Overview

Everything we deliver runs on trustworthy data. Your work is to turn fragmented client data into a foundation the rest of the team can build on. When a data scientist ships a model or an AI engineer deploys an agent, they rely on the pipelines you design. You own data up to the contract: getting it in, making it trustworthy, and serving it.

Responsibilities

• Design and run reliable pipelines at scale, both batch and streaming
• Architect data platforms including warehouses, lakes, lakehouses, and graph data foundations
• Own data quality, governance, lineage, and access
• Model data for operational and analytical use and stand up feature-store infrastructure
• Serve clean, documented data through clear contracts and build reusable foundations

Requirements

• Strong software discipline and MLOps mindset
• Systems thinking approach to data architecture
• Experience with containerized pipelines and observability
• Ability to work across different stacks and industries as a technology-agnostic engineer

Skills

• Python
• PySpark
• Airflow
• Databricks
• Postgres

Benefits

• Flexible schedule
• Work from home