Senior Data Engineer
Senior Data Engineer at IT services firm Accesa, building the customer data foundation for a client's Marketing AI personalization product. Day to day: designing customer data marts, real-time streaming between CDP/CEP systems, and Python REST APIs, using GCP (BigQuery, Pub/Sub, Dataform), Terraform and GitHub Actions.
- Compensation
- Not disclosed
- Location
- Canada
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 20+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Expert Python and SQL skills in production data engineering
- Hands-on experience with GCP data services (BigQuery, Pub/Sub, Cloud Run, 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
- Fluent English for working in an international team
Nice to have
- 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
Full description
The client is developing its own Marketing AI product to deliver personalized product, bundle, and promotion recommendations based on customer profiles, purchase history, and behavioral data. The goal is to make recommendations more relevant, increase conversion, and improve profit margins.
Within this initiative, we are looking for Data Engineering profiles, one focused on building the customer data foundation and another on integrating customer platforms and communication channels.
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.
Must have
- 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.
- Fluent English for working in an international team.
Nice to have
- 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.
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