Senior Data Engineer - AI Personalization & Customer Data

Overview

The AI Products and Platform (AIPP) team builds the foundational capabilities that enable AI-driven personalization, decisioning, and real-time customer experiences  work supports intelligent interactions across digital and assisted channels, helping ensure customers receive timely, relevant, and responsible experiences.

• Build and operate real-time data pipelines that ingest customer events (payments, app behavior, IVR interactions) and power ML product decisions across channels.
• Develop event-driven architectures using GCP services (Pub/Sub, Dataflow, Cloud Run, Big Query) to support low-latency triggers and segmentation.
• Partner with Data Scientists and ML engineers to product ionize AIPP models (e.g., ML2), transforming model outputs into reliable, explainable data feeds.
• Translate business and marketing requirements into scalable data logic, including customer segments, eligibility rules, and offer mappings.
• Enable IVR and CCAI experiences by supporting data flows for intelligent routing, proactive messaging, and self-serve journeys.
• Support internal tools and future UI capabilities by providing clean datasets, schemas, and APIs for Software and Full Stack Engineers.
• Monitor, troubleshoot, and improve production pipelines, ensuring data quality, reliability, and observability during peak periods.
• Optimize for performance and cost, balancing streaming workloads, Big Query usage, and API integrations.
• Enable responsible AI practices through validation, lineage, and monitoring so personalization decisions remain transparent and trustworthy.
• Contribute to long-term architecture and standards, helping AIPP evolve into a steady-state personalization platform.

• 4+ years of experience in Data Engineering or backend data systems.
• Strong experience with Python and SQL in production environments.
• Hands‑on experience with GCP, especially Big Query and Pub/Sub.
• Experience designing and operating streaming or event‑driven pipelines.
• Understanding of data modeling, data quality, and pipeline reliability.
• Experience integrating data via APIs, including retries, rate limiting, and failure handling.
• Bachelor’s degree in Computer Science, Engineering, Data Systems, or a related technical field OR equivalent hands‑on industry experience building production‑grade data pipelines.

• Experience with Adobe Experience Platform or other CDPs.
• Exposure to AI/ML feature pipelines or real‑time model scoring.
• Experience with Dataflow (Apache Beam), dbt, or Airflow/Composer.
• Familiarity with personalization or decisioning platforms (PEGA‑like concepts).
• Telecom or high‑volume consumer data experience.

Location:

Calgary, Alberta, Canada

Salary: CA$–CA$