As a Data Engineer with TELUS Digital, you will be responsible for crafting, building and running the data driven applications which enable innovative, customer centric digital experiences for TELUS customers. 

You will be working as part of a friendly, cross-discipline agile team who helps each other solve problems across all functions. As a custodian of customer trust, you will employ best practice in development, security, accessibility and design to achieve the highest quality of service for our customers. 

Our development team uses a range of technologies to get the job done: Spark, Sqoop and coupled with Oozie, shell scripting, Control-M to provide a modern, easy to use data pipeline. You will be part of the team building a data pipeline to transfer the data from our enterprise data lake for enabling our AI use cases. 

You are a fast learner, highly technical, hardworking data engineer looking to work within a team of multidisciplinary experts to improve your craft and contribute to the data development practice at TELUS Digital. 

Here’s how 

● Learn new skills & advance your data development practice 

● Design, develop, test, deploy, maintain and improve the analytics pipeline ● Assist in evaluating technology choices and rapidly test solutions 

● Assist the outcome teams in understanding how to best measure their web properties ● Collaborate closely with multiple team in an agile environment 

You're the missing piece of the puzzle 

● A passion for data 

● Interest and ability to learn new languages & technologies as needed ● Familiar with the execution sequence of ETL Flows 

● Experience with Spark, Sqoop, Oozie, Control-M 

● Basic understanding of data warehouse, data lake, OLAP and OLTP applications 

As a Data Engineer on the AIPP team, you’ll: 

● Build and maintain real-time and batch data pipelines that power NBS personalization

and ML arbitration. 

● Enable cross-channel event collection and orchestration (digital, IVR, billing, service disruption). 

● Work closely with AI/ML engineers to integrate self-serve propensity models and arbitration logic into production. 

● Ensure high-volume, low-latency streaming data processing to support millions of triggers per day. 

Great-to-haves 

● Experience with Google Cloud Platform 

● Experience with Big Data related tools and technologies 

● Experience with creating REST APIs in Python 

● Experience with data monitoring and alerting