Description
Our team and what we’ll accomplish together
The TELUS Business Solutions (TBS) organization is dynamic, fast-paced, and entrepreneurial. Together, the team is responsible for driving profitable growth within a key growth segment for TELUS: Small & Medium business (SMB).
Our Team – Lifecycle Marketing and Data Science - has a mandate to build solutions for our stakeholders using data to drive business outcomes. We love to turn data into stories - stories about money falling through the cracks, success stories about our products and services, but most importantly stories about our customers and how we can enhance their experience.
Come join our team if you have a passion for data, analytics, marketing, the courage to innovate, embrace change and embody spirited teamwork to support stakeholders across a wide variety of teams.
What you’ll do
As a Senior Data Engineering Consultant in the team, you will be working with Business Stakeholders and the Data Scientists to build data assets that will be leveraged by the data scientists for machine learning/AI models to protect the customer base, acquire new customers and to enable intelligent marketing campaigns. Your solutions will have a direct impact on marketing sales targets and P&L.
Design and build scalable and resilient Data Pipelines & Analytics solutions in Google Cloud Platform – architect technical solutions to obtain, process, store and provide insights based on processed data and ensuring the quality and availability of data for machine learning models, analytics, and critical business operations.
Build data assets for machine learning purposes on Google Cloud Platform
Work on automation and optimization of internal processes
Provide data analysis and standard reporting support
Design, develop, and review data architecture, model, flow, and integration – be hands on and involved with every stage of the ETL pipeline
Keep up to date with the evolving Cloud technology and Big Data technology, share the knowledge across the organization by enabling best practices, standards, governed processes and relevant technologies
Perform technical data stewardship tasks including metadata management, security and privacy by design
Qualifications
Bachelor's Degree in Software Engineering, Computer Science, Business or related field
Data engineering certification
6+ years of experience in big data analytics and distributed systems
4+ years data platform solution architecture and design
Experience in writing code/ETL processes/Monitoring processes on Google Cloud Platform
Knowledge of Big Data with a focus on data engineering; optimizing data, pipelines, ETLs
Experience implementing production level deployments at an enterprise scale on Google Cloud Platform
Strong coding and development skills in programming languages (e.g. Python, PySpark etc.)
Strong understanding of data structures, databases, data lakes, and data ingestion and transformation routines
Advanced experience with Python and mastery of data manipulation libraries (like Pandas), paired with strong SQL skills for complex querying and data analysis
Great-to-have
Design, develop, and deploy end-to-end AI/ML models using GCP services
Experience in MLOps, supporting the data infrastructure required for machine learning workflows
Machine Learning and AI models, including classification, clustering, time series analysis, NLP, optimization, and deep learning experience or knowledge
Post graduate education in Data, Advanced Analytics, Computer Science Engg/Programming or any other relevant program
Certification on Google cloud or any other cloud platform
Telecom industry experience
