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Data Visualization Jobs in Alberta (NOW HIRING)

Data Visualization & Dashboards : Design and build intuitive, visually compelling dashboards and reports in Looker Studio that communicate complex data stories to diverse stakeholders. Create data ...

Data Visualization & Dashboards : Design and build intuitive, visually compelling dashboards and reports in Looker Studio that communicate complex data stories to diverse stakeholders. Create data ...

Data Visualization * Predictive Analysis * Statistical Modeling * Data Mining * Clustering & Classification * Data Analytics * Quantitative Analysis * Web Scraping * Model Development ...

Prepare data sets for visualization and machine learning modeling. Train machine learning systems using data annotation and benchmarking techniques. Help your colleagues assess AI/ML model ...

Responsibilities • Gain proficiency in exploratory data analysis, perform it, and present insights. • Prepare data sets for visualization and machine learning modeling. • Train machine learning ...

Responsibilities • Gain proficiency in exploratory data analysis, perform it, and present insights. • Prepare data sets for visualization and machine learning modeling. • Train machine learning ...

Advanced Excel skills (pivot tables, formulas, data visualization). * Familiarity with business intelligence or reporting platforms an asset. Skills & Competencies * High attention to detail and ...

Advanced Tableau proficiency for dashboard creation and data visualization Intermediate knowledge of English is required because you will most of the time interact in English with external parties ...

Advanced Tableau proficiency for dashboard creation and data visualization Intermediate knowledge of English is required because you will most of the time interact in English with external parties ...

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Data Visualization information

What Is Data Visualization?

Data visualization is the process of taking statistical data and preparing it in a visual context that is easier to understand. You use software and graphics to demonstrate patterns, correlations, and trends that appear more significant when viewed outside of a written context. Visual representation comes in the form of infographics, heat maps, geographic maps, and detailed pie or bar charts. Business intelligence recognizes the need for appropriate colors and images and is now standard for modern organizations. Data visualization is also a reporting tool that tracks performance and generates dashboards to observe click-through rates digital marketing campaigns.

Is 40 too late for data science?

Data visualization is a key skill in data science, and individuals can successfully transition into this field at any age, including 40. Building relevant skills such as proficiency in tools like Tableau or Power BI, along with foundational knowledge in statistics and programming, can facilitate entry regardless of age, as employers value experience and diverse perspectives.

Can I be a data analyst with no experience?

Data analysts typically need some familiarity with data analysis tools like Excel, SQL, or visualization software such as Tableau. While prior experience is often preferred, entry-level positions may be available for those who demonstrate strong analytical skills and a willingness to learn through courses or certifications. Building a portfolio of projects can also improve chances of securing a data analyst role without formal experience.

What is the difference between Data Visualization vs Data Analyst?

AspectData VisualizationData Analyst
Primary FocusCreating visual representations of dataAnalyzing and interpreting data
SkillsData visualization tools, graphic design, storytellingStatistical analysis, Excel, SQL, data interpretation
ToolsTableau, Power BI, D3.jsExcel, SQL, R, Python
Work EnvironmentDesign-focused, often collaborative with data teamsAnalytical, research-oriented, cross-departmental

Data Visualization specialists focus on creating visual representations to communicate data insights effectively, while Data Analysts analyze data to uncover trends and inform decisions. Both roles often collaborate but serve different core functions within data-driven organizations.

What is data visualization?

Data visualization is the process of representing data and information in a graphical or pictorial format, such as charts, graphs, or maps. This practice helps people understand complex data sets more easily by highlighting patterns, trends, and outliers. Data visualization is widely used in various industries to support decision-making, communicate insights, and make data more accessible to a broader audience.

Is data visualization a good career?

Data visualization is a valuable career in data analysis and business intelligence, involving creating visual representations of data using tools like Tableau, Power BI, or Python. It requires strong analytical skills, knowledge of data tools, and the ability to communicate insights effectively, making it a growing field with demand across many industries.

What are some common challenges faced by professionals in Data Visualization roles, and how can they be addressed?

Professionals in Data Visualization often encounter challenges such as translating complex datasets into clear, meaningful visuals and ensuring that visualizations are both accurate and accessible to diverse audiences. Balancing aesthetic appeal with functionality can also be demanding, as visuals must communicate insights without causing confusion. To address these challenges, effective collaboration with data analysts, subject matter experts, and end-users is essential, as is staying current with best practices and visualization tools. Regular feedback and iteration help refine visualizations to best meet stakeholders' needs.

What are the key skills and qualifications needed to thrive as a Data Visualization Specialist, and why are they important?

To thrive as a Data Visualization Specialist, you need strong analytical abilities, a solid foundation in statistics, and proficiency with data visualization principles, typically supported by a degree in data science, computer science, or a related field. Familiarity with visualization tools such as Tableau, Power BI, or D3.js, and experience with data processing languages like Python or R, are commonly required. Creativity, attention to detail, and effective communication skills help convey complex data insights clearly to diverse audiences. These skills ensure that data is transformed into actionable, visually compelling insights that drive informed decision-making within organizations.

What jobs do data visualization?

Data visualization jobs include roles such as data analyst, data scientist, business intelligence analyst, and data visualization specialist. These positions involve creating visual representations of data using tools like Tableau, Power BI, or Python to help organizations interpret complex information and support decision-making.
What are the most commonly searched types of Data Visualization jobs in Alberta? The most popular types of Data Visualization jobs in Alberta are:
What are popular job titles related to Data Visualization jobs in Alberta? For Data Visualization jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Data Visualization jobs in Alberta look for? The top searched job categories for Data Visualization jobs in Alberta are:
What cities in Alberta are hiring for Data Visualization jobs? Cities in Alberta with the most Data Visualization job openings:
Infographic showing various Data Visualization job openings in Alberta as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.
Data Scientist

Data Scientist

TELUS

Edmonton, AB • On-site

Other

Posted 6 days ago


TELUS rating

8.2

Company rating: 8.2 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

24th of 96 rated telecommunications companies


Job description

Description

Be a part of a transformational journey with innovative talent and leading edge technologies.


Join our team and what we'll accomplish together

This is an exciting opportunity to join the Systems Simplification Innovation Hub within Systems Simplification Team. We are a dynamic and agile team revolutionizing TELUS operations by designing data-driven solutions that optimize OpEx, CX, sales, billing, and other key metrics across our national workforce. Our Data Analytics team is the go-to destination for analytical, creative professionals passionate about developing their talents while solving some of TELUS' most significant challenges.

What you'll do

As a Data Scientist, you'll work closely with stakeholders and software engineers to identify and implement scalable data architectures, transform raw data into actionable insights, and create compelling visualizations that drive business decisions across TELUS. 


Your Responsibilities: 

  • Data Architecture & Engineering: Design and build robust data pipelines and architectures on Google Cloud Platform (GCP), leveraging BigQuery, Workflows, Cloud Scheduler, Dataproc, and Batch jobs. Establish scalable ETL/ELT processes that efficiently ingest, transform, and prepare data from diverse sources for analytics and reporting. Build and manage GCP resources using Pulumi and YAML configurations, and maintain code in GitHub.
  • Advanced Analytics & Insights: Conduct in-depth exploratory data analysis and apply statistical methods, machine learning techniques, and AI-driven analytics to uncover patterns, trends, and actionable business insights. Develop analytical models and leverage AI capabilities to support strategic decision-making and operational improvements across key business metrics.
  • Data Visualization & Dashboards: Design and build intuitive, visually compelling dashboards and reports in Looker Studio that communicate complex data stories to diverse stakeholders. Create data visualizations with a strong eye for clarity, aesthetics, and user experience that enable self-service analytics.
  • GCP Platform Expertise: Leverage GCP's data ecosystem (BigQuery, Workflows, Cloud Scheduler, Dataproc, Batch, and Vertex AI) to optimize query performance, reduce costs, and enable real-time analytics. Implement best practices for data governance, security, and scalability within GCP environments.
  • Collaboration and Mentoring: Work with business teams and stakeholders to understand data requirements and translate business questions into analytical solutions. Document analytical findings and architectural decisions clearly, and mentor team members on data best practices.
Qualifications


What you bring

  • Master's degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative discipline - or a PhD in a relevant field.
  • 3+ years of experience designing and implementing data architectures and analytics solutions in production environments, delivering measurable business impact.
  • Advanced proficiency in Google Cloud Platform (GCP), with hands-on experience in BigQuery, Workflows, Cloud Scheduler, Dataproc, and Batch jobs.
  • Expert-level experience with Looker Studio for creating dashboards, reports, and data visualizations that drive business insights and support decision-making.
  • Strong foundation in data architecture and ETL/ELT design, with the ability to optimize data pipelines for performance, scalability, and cost efficiency.
  • Demonstrated expertise in data visualization and analytics, with a keen eye for designing clear, compelling, and actionable insights that resonate with both technical and business audiences.
  • Experience working in GitHub, building and managing GCP resources using Pulumi and YAML configurations.
  • Strong SQL skills and experience working with large-scale datasets; proficiency in data modeling and dimensional design.
  • Proven experience analyzing structured and unstructured data using statistical methods, exploratory data analysis, and machine learning techniques to drive insights.
  • Proficiency in Python or similar languages for data processing and analytics.
  • Experience leveraging AI capabilities and tools (such as Vertex AI) to build machine learning models and AI solutions that enhance analytical capabilities.
  • Experience deploying and monitoring data solutions in production, with familiarity in CI/CD, version control, and cloud infrastructure best practices.
  • Strong ability to translate business questions into analytical frameworks and communicate findings effectively with both technical and non-technical stakeholders.

What TELUS employees say

Pay

Hours and flexibility

Workplace

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