Senior Data Engineer

The role is the single owner of the data platform behind a camera and scale product used in many kitchens. That covers moving images and weights from devices in kitchens, through AI models, into dashboards and customer access points. A strong candidate has six or more years of data engineering, has built data foundations from scratch, and is solid in Python, SQL, Google Cloud and BigQuery, with infrastructure written as code and some streaming experience.

How it fits the AI era

AI changes the daily work by taking over boilerplate, debugging and routine tasks, so more time goes to design choices. The platform itself exists to feed AI models with clean data and to open data to AI tools through APIs and MCP servers. What stays human is judging trade-offs, taking responsibility when systems fail in real use, and explaining decisions clearly to analysts, engineers and AI specialists.

How it builds AI experience

Someone in this seat would see how a large image dataset from the real world is collected, cleaned and fed back into a production vision model. They would also gain hands-on practice building MCP servers and access-controlled APIs for AI tools. To prepare, build a small project that streams data into BigQuery, then expose it through an API or MCP server with permissions.

Worth showing

• BigQuery and Dataform pipelines
• Streaming with Apache Beam
• Terraform infrastructure as code
• Using AI tools to build faster

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Orbisk

Per the company, Orbisk makes an AI-powered food waste monitor that helps professional kitchens cut waste and costs.