About Us : At TELUS Digital, we enable customer experience innovation through spirited teamwork, agile thinking, and a caring culture that puts customers first. TELUS Digital is the global arm of TELUS Corporation, one of the largest telecommunications service providers in Canada. We deliver contact center and business process outsourcing (BPO) solutions to some of the world's largest corporations in the consumer electronics, finance, telecommunications and utilities sectors. With global call center delivery capabilities, our multi-shore, multi-language programs offer safe, secure infrastructure, value-based pricing, skills-based resources and exceptional customer service - all backed by TELUS, our multi-billion dollar telecommunications parent. Key Responsibilities:Design, develop, and maintain scalable and efficient ETL pipelines to extract data from various sources, transform it, and load it into Google BigQuery.Write high-quality, maintainable Python code for data processing and transformation, leveraging core libraries such as Pandas and NumPy.Author and troubleshoot complex SQL queries to support data extraction, transformation, and analysis within our data warehouse.Collaborate with team members and stakeholders in an Agile/Scrum environment to deliver features in sprints.Provide post-deployment support for your developed solutions for a 3-month "warranty period," which includes monitoring jobs, identifying issues, and deploying fixes.Engage with teams in different time zones (primarily Central America) for requirements clarification and issue resolution, requiring some flexibility in work hours.Contribute to the overall architecture and design of our data solutions, ensuring they are robust and performant. Qualifications & Skills:Must-Have:Experience: 3-5 years of professional experience in a data warehousing, ETL development, or data engineering role.Database Expertise: Expert-level proficiency in SQL. You must be able to write, optimize, and troubleshoot complex queries, including multi-level joins, window functions, and aggregations.Python Proficiency: Strong, hands-on experience using Python for ETL and data manipulation. Demonstrable expertise with data-centric libraries, specifically Pandas and NumPy, is required.ETL Fundamentals: A deep understanding of ETL principles, data modeling, and data warehouse architecture. Preferred & Advantageous:Cloud Experience: Hands-on experience with Google Cloud Platform (GCP), particularly BigQuery.Alternative Cloud Skills: Experience with other cloud platforms like AWS (Redshift) or Azure (Synapse Analytics) is a significant plus.BI Tool Familiarity: Experience with any BI visualization tool (e.g., Tableau, Looker, Sisense, Power BI, Cognos) is considered a valuable secondary skill.Agile Methodology: Prior experience working in an Agile/Scrum development team.
