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 d...