GCP Data Warehouse Engineer – AI-First, Hybrid

Bet365careers; Manchester; Hybride; GBP 65 000 - 90 000; Plein temps

Résumé du poste

bet365 in Manchester is seeking a Data Warehouse Developer to help build scalable cloud data platforms and real-time analytics. The role focuses on enterprise data warehouse and data catalogue enhancements in a fully cloud-based, AI-first environment.

You will collaborate with architects and developers to design robust data models and modern pipelines, delivering immediate value to data consumers while meeting tight deadlines.

Qualifications

• Experience with Google Cloud Platform (GCP) in production.
• Deep knowledge of BigQuery, Cloud Composer, Analytics Hub and BigLake.
• Hands-on with AI technologies and enterprise AI agents.
• Proficient with data catalog solutions.
• Strong SQL and relational data modelling skills.
• Experience with Data Lake and Data Warehouse architectures.
• Dimensional modelling for enterprise DW.

Responsabilités

• Manage and optimise Google Cloud Platform components, including BigQuery, Composer, Analytics Hub and BigLake
• Develop and maintain scalable transform processes feeding into the central data warehouse
• Define and implement robust engineering processes and architectural standards across GCP products
• Produce and maintain clear technical documentation for warehouse assets and pipelines
• Drive adherence to development standards and best practice throughout the engineering lifecycle

Connaissances

GCP

BigQuery

Cloud Composer

Analytics Hub

BigLake

AI tech

Data catalog

SQL

Data Lake/Warehouse

Dimensional modeling

Problem solving

Description du poste

bet365 in Manchester is seeking a Data Warehouse Developer to help build scalable cloud data platforms and real-time analytics. The role focuses on enterprise data warehouse and data catalogue enhancements in a fully cloud-based, AI-first environment.

You will collaborate with architects and developers to design robust data models and modern pipelines, delivering immediate value to data consumers while meeting tight deadlines.