Senior Data Engineer - AI Personalization & Real-Time Customer Data
Calgary, AB, CA Toronto, ON, CA
Join our team and what we'll accomplish together
The AI Personalization Platform (AIPP) team powers TELUS’ real-time, AI-driven personalization across App, Web, SMS, and CCAI IVR. Our mandate is to enable responsible, scalable personalization by ensuring the right data reaches the right system at the right moment. We work at the intersection of data engineering, machine learning, and customer experience, supporting high-impact initiatives such as real-time triggers, ML v2 (ML2) models, and intelligent IVR experiences. Our work directly contributes to TELUS’ 2026 personalization strategy and measurable customer and revenue outcomes.
We are hiring a Data Engineer to strengthen the data foundations that power real-time decisioning and AI-driven personalization. This is a hands-on engineering role focused on event-driven pipelines, customer segmentation, and data ingestion, not dashboarding or offline analytics.
You will partner closely with Data Scientists, Product Managers, IVR/CCAI teams, and Software Engineers to productionize ML models, enable real-time triggers, and support internal tooling (such as future offer-loading or segmentation UIs). This role replaces a critical data engineering position on the team and is foundational to delivering committed 2026 benefits.
What you will do:
- 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, BigQuery) to support low-latency triggers and segmentation.
- Partner with Data Scientists and ML engineers to productionize 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, BigQuery 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.
What you bring
- 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 BigQuery 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
Nice to Have:
- 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