Data Management - Virtual Position
Vancouver, BC, CA, V6B 0M3
Description
We strategically enable our field team members to be as efficient as possible by maximizing field outforce potential, increasing productivity, and identifying areas of opportunity.
As Data Management Professional within the National Operations Excellence team, you will support business operations by working directly with members of the same team, other teams across multiple functions and management to understand, prioritize and collaborate in providing the field with accurate data driven insights
We are looking for a results-driven individual with a passion for process design, analytics, and storytelling through data. Our team is diverse and dynamic, offering work-life flexibility, collaborative decision-making and support, and opportunities to learn from and influence decisions across a vast network of experienced operations-focused team members. Join us to be part of an inspiring and rewarding team!
What you’ll do
As a Data Management Professional, you will have a crucial role in developing, implementing, and monitoring new KPIs and reports to support TELUS CSD field operations. You will be responsible for planning, managing, and delivering analytical insights that focus on achieving integration and improving efficiencies within TELUS field operations.
- Your contribution will be fundamental in creating a highly agile, productive, and efficient field operations team. As a result, you will be able to play an essential role in supporting TELUS's ongoing commitment to delivering the best possible service to our customers
- Assist the National Operations Excellence team with facilitation of data deep dives regarding first order success, field productivity, order reliability, and workmanship quality
- Create, ideate, and execute upon dashboard designs that will provide management with self-servable insights to properly manage field operations
- Collaborate with the National Operations Excellence team on rolling out new efficiency enhancing projects and programs
- Act autonomously to identify areas of improvement across but not limited to: data best practices, data visualization, analysis techniques, redundancy reduction, and implementing statistical concepts
- Collaborate effectively and efficiently across multiple disciplines, organizational boundaries, and stakeholder groups
- Deliver impactful, concise, and effective communications and presentations to all levels of the business both internally and externally
What you bring
- Experience with data visualization tools like Tableau, Domo, Looker or Google Data Studio; including experience with dashboard design, and report development
- Familiarity with Google BigQuery, Google Cloud Storage, and Google Dataflow
- Demonstrated proficiency in SQL and Python
- Basic knowledge of machine learning algorithms and frameworks (e.g., TensorFlow, scikit-learn)
- Experience with Jupyter Notebooks or Google Colab
- Business Management - KPI development and inspection, business planning and execution
- Understanding of enablement, marketing, business and financial acumen
- Expertise in database design, including experience with complex queries, stored procedures, and performance tuning
- Able to analyze large datasets and create efficient queries to retrieve and manipulate data
- Experience in integrating data from multiple sources and creating data models that support self-service analytics
- Experience in automating workflows and tasks using Google Apps Script and APIs
Qualifications
Great-to-haves
- Highly organized with a demonstrated ability to delegate, monitor and manage high volume workloads
- University Degree or Technical Diploma – asset or equivalent experience
- Google Cloud Professional Data Engineer certification AND/OR Google Cloud Professional Machine Learning Engineer certification
- Demonstrated expertise in managing cloud infrastructure as code using Pulumi, proficiency in writing and managing YAML configurations for various tools and services, and working knowledge of GitHub, including branching strategies and CI/CD pipelines
- Experience with TELUS Virtual Private Cloud (VPC) architecture and security controls is an asset
- Experience with machine learning concepts and techniques such as regression and clustering
- Knowledge of machine learning algorithms and frameworks (e.g., TensorFlow, scikit-learn)
- Experience with programming languages such as Python or R for data analysis and modeling
- Strong knowledge of statistics and quantitative analysis techniques
- Bilingualism (English & French)