Telus AI has an exciting opportunity for a Data Architect to come on board to support our work with the largest global tech customers. Access to large datasets and the opportunity to engage with innovators that are driving new customer solutions.
Role Description
You will be working with the Telus Digital business helping to shape the analytics function. You will get the opportunity to work on large datasets that are generated from our global communities working with some of the largest global tech customers in the world. The Insights shared back to our customers can provide impactful changes to consumers located across the globe through required products used in everyday life.
You will work closely with internal functions and the business leadership to design, develop and maintain data models (with all of the required underlying architecture) to support BI and analytical solutions.
Responsibilities
1. Develop an in-depth understanding of the business processes. Use that knowledge and customer-centric approach to develop and implement an architecture, solutions and data models to improve and support the business processes.
2. Develop a data strategy and roadmap working to identify digital transformation needs that will drive value.
3. Mentor data analysts and engineers to drive the implementation of this roadmap.
4. Lead the data analytics team in the delivery of an architecture that continues to evolve and embrace the advantages of new technologies and pipelines as they become available.
5. Improve data quality and foster a culture of accountability and continuous improvement.
6. Support data governance across programs.
Skills & Experience
1. Bachelor’s Degree in Computer Science, Information Technology or related technical field.
2. 3 plus years of experience in architecture design and implementation.
3. 3 plus years of experience in leading data projects and teams to deliver value.
4. Experience in strategic planning and aligning data projects with business goals and the ability to communicate that strategy vision clearly.
5. Proven ability to mentor a diverse team of data analysts, engineers and scientists to ensure an understanding of the data ecosystem.
6. Expertise in designing and implementing complex data models in BI tools such as Sisense.
7. Knowledge of cloud-based databases like BigQuery, traditional relational databases (e.g., Oracle, MySQL, SQL Server), and familiarity with technologies such as GCP.
8. Proficiency in programming languages (e.g., Python, R, SQL).
9. Strong understanding of data warehouse and data governance.
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