Build reliable data foundations for restaurant reporting, product decisions and useful AI capabilities.
About the role
Order and payment data only becomes useful when people can understand and trust it. You will work on the pipelines, transformations and access patterns that make data dependable for analysts, engineers and the teams making business decisions.
The difference you’ll make
- Teams can trace data from its source to the numbers they use.
- Data workflows are repeatable and easier to operate.
- Analysts and engineers spend less effort untangling how data fits together.
What you’ll do
- Design production data pipelines for ingestion, transformation, storage and orchestration.
- Replace fragile one-off processes with reproducible, maintainable data workflows.
- Improve data quality and consistency so reporting and product decisions rest on a clear foundation.
- Help analysts and engineers access useful data through understandable, well-managed interfaces.
- Investigate performance and cost, review code and explain technical choices to colleagues across the business.
What you’ll bring
- 5+ years of data engineering or analytics engineering experience.
- Strong SQL and Python skills and practical experience with reliable production data systems.
- A solid understanding of ETL/ELT, data transformation, warehouses and workflow orchestration.
- The ability to investigate quality and performance issues, create structure and explain decisions to technical and nontechnical colleagues.
It’s a plus if you have
- Experience with tools such as Snowflake, dbt, Dagster or Airflow.
- Experience with semantic layers, reverse ETL or data infrastructure for AI and machine learning.
- Experience with access controls, data governance, cost optimization or mentoring engineers.
