Descrizione
Responsibilities: Design and build a scalable customer data mart that consolidates loyalty attributes, wishlist and affinity data, and explicit preferences captured in the app. Set up real-time data streaming between backend systems, the CDP (Zeotap) and the CEP (Responsys). Build and maintain robust backend APIs that give product teams access to customer data for personalization.
Model and transform data in BigQuery and Dataform, and orchestrate pipelines with Cloud Workflows, Cloud Scheduler and Eventarc. Manage infrastructure as code with Terraform and ship through CI/CD pipelines in GitHub Actions.
Requirements
Expert Python and SQL skills in production data engineering. Hands-on experience with GCP data services, in particular BigQuery, Pub/Sub, Cloud Run and Cloud Storage. Experience with Dataform, Datastore, Cloud Workflows, Eventarc and Cloud Scheduler.
Experience building real-time or event-driven data pipelines. Experience designing data models and data marts for analytical and operational use. Experience building REST APIs in Python, ideally with Flask.
Infrastructure as code with Terraform (HCL) and CI/CD with GitHub Actions. Experience integrating a Customer Data Platform (Zeotap). Experience with Oracle Responsys or another CEP (Salesforce Marketing Cloud, Braze).
Background with customer, loyalty or e-commerce data, including identity resolution. GCP Professional Data Engineer certification. Fluent English for working in an international team.
At Accesa: We nu
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