
Data Architect for Scalable Business Solutions
1 day ago
Data Engineer at TELUS Digital
About Us
TELUS Digital Experience partners with the world's most innovative brands, from tech startups to industry leaders in fintech, gaming, healthcare, and more. We empower businesses to scale and redefine possibilities with integrated customer experience and cutting-edge digital solutions.
Backed by a multi-billion-dollar parent company, we offer scalable, multi-language, and multi-shore capabilities. Our expertise spans digital transformation, AI-driven consulting, IT lifecycle management, and more – delivered with secure infrastructure, value-driven pricing, and exceptional service.
Ai Data Solutions: Shaping the Future of Ai
For nearly two decades, our Ai Data Solutions has been a global leader in providing premium data services for the ever-evolving Ai ecosystem. From machine learning to computer vision and Generative Ai (GenAi), we empower the next generation of Ai-powered experiences with high-quality data and human intelligence to test, train, and improve Ai models.
Backed by a community of over one million contributors and proprietary Ai-driven tools, we deliver solutions designed to cover the training data needs of every project. From custom data collection to advanced data annotation and fine-tuning, our purpose-built tools deliver multimodal data for Ai training projects of any complexity – from experimental pilots to ambitious large-scale programs. Examples include empowering GenAi models with human aligned datasets and fine-tuning data across 20+ domains and 100+ languages, enabling autonomous driving and advancing extended reality applications with industry-leading data labeling.
Key Responsibilities:
- Build, deploy, and manage data pipelines using Python and PySpark
- Develop and optimize ETL/ELT processes to support data integration across systems
- Work directly with GCP and AWS services to implement scalable cloud-based data solutions
- Own data workflows end-to-end – from ingestion to transformation to storage
- Continuously monitor and improve pipeline reliability, speed, and data quality
- Use GenAi and automation tools to speed up development and reduce manual effort
- Proactively debug, troubleshoot, and resolve data engineering issues
- Ensure data is available and trustworthy for analytics and downstream systems
- Deliver high-quality code and documentation with a bias for action
Required Skills & Qualifications:
- Strong proficiency in Python and PySpark
- Working experience with cloud platforms like GCP and/or AWS
- Solid understanding of ETL/ELT, data warehouse and data lake concepts.
- Proficient in working with relational databases—preferably PostgreSQL and MySQL—as well as non-relational databases, with a focus on MongoDB.
- Driven by delivery and results — you get things done efficiently
- Self-starter attitude with minimal need for hand-holding
- Excitement for automating work using GenAi or scripting tools
- Familiarity with SCD, CDC, Real-time Streaming vs Batch-processing.
Benefits:
- High-impact role where execution speed is valued and recognized
- Freedom to build, ship, and iterate without red tape
- Work with a lean, high-performing data team
- Opportunities to innovate with Generative Ai tools
- Fast learning environment and ownership from day one
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