Data Engineer
Summary
Build and optimize cloud data pipelines on GCP to deliver reliable, scalable analytical datasets for analysts and data scientists using BigQuery, Python, and SQL.
Design, build and improve the cloud data pipelines and architectures that give analysts and data scientists trusted, usable data. This is a hands‑on opportunity to strengthen reliability, scale and cost efficiency while turning varied operational data into dependable analytical products.
Profile for success
- Demonstrated delivery of production data pipelines using Google Cloud Platform, BigQuery, Python and SQL.
- Evidence of designing and maintaining ETL processes that transform varied source data into structured analytical datasets.
- Experience building or improving data models, with clear ownership of data quality, validation and lineage.
- Examples of diagnosing and improving pipeline performance, scalability or cost.
- Strong hands‑on exposure to Dataflow, Pub/Sub and Cloud Storage is advantageous.
- Clear communication and collaboration with technical and non-technical data users.
- A relevant degree is preferred, supported by at least five years of relevant data‑engineering experience.