Posted:2 weeks ago|
Platform:
Hybrid
Full Time
We are looking for a hands-on, action-oriented Data Engineer who thrives on execution.
This role is perfect for someone who enjoys rolling up their sleeves, building robust data
pipelines, and delivering solutions that directly impact the business. If you prefer doing
over discussing, and value outcomes over process, we want you on our team.
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
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.
Experience with CI/CD pipelines and Docker
Understanding of data governance and observability
Prior experience in fast-paced, execution-heavy teams
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
Regards,
Aayushi Agrawal
TELUS International
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