ZipRecruiter

Log In

1

Analytics Engineer Jobs in Alberta (NOW HIRING)

PwC

AI & Advanced Analytics, Senior Manager

Calgary, AB

CA$168K - CA$218K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Krux Analytics

Data Architect

Calgary, AB · On-site

Bachelor's Degree (Computer Science, Technology, Engineering, or related field) * 10+ years of experience as a data analytics developer or engineer * 5+ years of experience in developing data ...

Takeaway

Senior Manager - Data Engineering

Calgary, AB · On-site +1

CA$120K - CA$160K/yr

Lead the build-out of Canada's Gold/semantic consumption layer with data contracts and SLAs, and retire the legacy analytics warehouse. * Partner with the Lead Data Engineer on system design of our ...

SNC-Lavalin

Reporting Lead

Calgary, AB · On-site

Lead a team of reporting analysts, developers, and third-party partners. * Define and maintain semantic models, reporting data structures, and trusted data sources. * Drive adoption of modern ...

next page

Showing results 1-20

All JobsAnalytics Engineer JobsAnalytics Engineer Jobs in Alberta

Analytics Engineer information

What do analytics engineers do?

Analytics engineers design, build, and maintain data pipelines and infrastructure to enable data analysis and reporting. They work with tools like SQL, Python, and data warehouses to ensure data is accurate, accessible, and well-structured for analysts and data scientists. Their role often involves collaborating with teams to optimize data workflows and ensure data quality.

What are the key skills and qualifications needed to thrive as an analytics engineer, and why are they important?

To thrive as an Analytics Engineer, you need a strong foundation in data modeling, SQL, and analytics engineering principles, often supported by a degree in computer science, data science, or a related field. Proficiency with data transformation tools such as dbt, cloud data warehouses like Snowflake or BigQuery, and version control systems like Git is essential. Strong problem-solving skills, communication, and collaboration abilities help translate business needs into scalable data solutions and foster teamwork. These skills and qualities are crucial for ensuring data quality, building reliable analytics infrastructure, and enabling data-driven decision-making across organizations.

What is the difference between Analytics Engineer vs Data Engineer?

AspectAnalytics EngineerData Engineer
CredentialsOften requires SQL, Python, data modeling certificationsRequires similar skills, often with additional focus on infrastructure and systems
Work EnvironmentFocuses on data analysis, visualization, and reportingBuilds data pipelines, manages data infrastructure
Industry UsageCommon in analytics teams, BI, and data-driven rolesPrevalent in data engineering, data platform teams

While both roles work closely with data, Analytics Engineers primarily focus on transforming data for analysis and visualization, whereas Data Engineers build the infrastructure and pipelines that enable data access. Understanding these differences helps in choosing the right career path or job role.

How does an analytics engineer typically collaborate with data scientists and business stakeholders on projects?

Analytics Engineers play a critical bridge role between data engineering and data analysis. They work closely with data scientists to transform raw data into clean, reliable datasets that are ready for advanced analytics or modeling. At the same time, they collaborate with business stakeholders to understand reporting needs, ensuring that data models align with business goals. Regular communication and iterative feedback are key, as Analytics Engineers often gather requirements, build data pipelines, and adjust data products based on stakeholder input.

What is an analytics engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis. They are responsible for designing, building, and maintaining data models, pipelines, and analytics tools that enable organizations to make data-driven decisions. Analytics Engineers often work closely with data analysts and business stakeholders to ensure clean, reliable, and well-structured data is available for reporting and analysis. Their work typically involves using SQL, data transformation tools like dbt, and cloud data warehouses to create scalable and efficient data solutions.
What job categories do people searching Analytics Engineer jobs in Alberta look for? The top searched job categories for Analytics Engineer jobs in Alberta are:
Analytics Engineer jobs near you
Infographic showing various Analytics Engineer job openings in Alberta as of August 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 81% In-person, and 19% Remote job distribution.

Senior Analytics Engineer, Analytics Enablement

Fullscript

Calgary, AB

Full-time

Retirement, PTO

Re-posted 24 days ago

Job description

About Fullscript

We're an industry-leading health technology company on a mission to help people get better. We started in 2011 with one simple idea. Make it easier for practitioners to access the products they trust so they can deliver better care.
 
That simple idea grew into a platform that powers every part of care. Today, more than 125,000 practitioners use Fullscript for clinical insights, lab interpretations, patient analytics, education, and access to high-quality supplements. Over 10 million patients rely on Fullscript to stay connected to their care plans and follow through on treatment.
 
We build tools that make care smarter and more human. Tools that save time, simplify decisions, and help practitioners stay closely connected to the people they care for. When everything they need is in one place, they can focus on what matters most: helping people get better.
 
This is your invitation.
 
Bring your ideas, your grit, and your care for people.
Join us and shape the future of care.

The Opportunity

We're hiring a Senior Analytics Engineer, Analytics Enablement to help Fullscript scale how teams access, use, and learn from data.

This role is centered on a specific problem: making it easier for people across Fullscript to self-serve trustworthy data without relying on analysts or data scientists for every question. That means understanding where teams get stuck, identifying common patterns in what they need, and building the tooling, assets, workflows, and enablement practices that help them do more on their own.

Your focus will be on improving the systems around data access and usage so teams across the company can find the right data, use the right tools, and build the confidence to answer more questions themselves.

A big part of that work is enablement. You'll teach people how to use analytics tools, how to find and work with the right datasets, how to approach analysis more effectively, and how to get from a question to an answer using the tools available. In some cases, you may create starter assets, examples, or shared patterns. The focus is on building repeatable tools and processes that help more people answer their own questions over time.

This role is a strong fit for someone who enjoys working across stakeholder groups, thinking in systems, and building practical solutions that combine BI tooling, data infrastructure, and user training.

What you'll do
  • Partner with stakeholders across Fullscript to understand recurring data needs, self-serve gaps, and patterns that can be solved through shared tooling and reusable assets
  • Design and implement self-serve analytics solutions such as trusted datasets, reporting foundations, templates, and workflows that make data easier to access and use independently
  • Improve how data is surfaced and consumed through BI tools and internal tooling, with a focus on usability, consistency, trust, and adoption
  • Use SQL, Python, and BI platforms such as Looker to build scalable solutions, including AI-powered analytics tools built internally
  • Create and deliver training, documentation, office hours, and hands-on enablement sessions that teach teams how to use tools, find data, and analyze it effectively
  • Partner with Analytics, Data Science, and Data Engineering to strengthen the infrastructure, patterns, and definitions that support self-serve analytics across the business
  • Own projects end-to-end from discovery through implementation, including ambiguous problems where the right approach isn't obvious

What you bring to the table

  • 5+ years of experience in analytics, business intelligence, analytics engineering, data science, or a related data role
  • Strong hands-on SQL skills and working proficiency in Python
  • Experience with BI and analytics tools such as Looker, Tableau, Power BI, or similar platforms
  • Experience building reusable data assets, self-serve analytics workflows, internal tooling, or reporting foundations that scale beyond ad hoc requests
  • Experience teaching, training, mentoring, or enabling others to use data tools and analytics resources with more confidence and independence
  • Strong communication skills and a consultative working style, with the ability to turn recurring business needs into practical, scalable solutions
  • The judgment and autonomy to manage moderately complex work independently while collaborating effectively across technical and non-technical teams

Bonus if you have

  • Experience with natural language or AI-powered analytics tools such as Flurry
  • Experience working in a modern cloud data environment
  • Experience partnering closely with Data Engineering or Analytics Engineering teams
  • Experience designing enablement programs or adoption strategies for BI tools or internal data products

Why this role matters

As Fullscript grows, so does the number of people who need access to reliable data to make good decisions. The long-term answer is not to route every question through a centralized team. It's to build better systems, clearer patterns, and stronger data fluency across the company.

What we can offer you

  • Salary range: $110,000 to $140,000 CAD
  • Flexible PTO and competitive pay, because work-life balance matters
  • RRSP/401k match and stock options to invest in your future
  • Premium benefits package with customizable coverage, paramedical services, and an HSA.
  • Fullscript discounts to save on high-quality wellness products
  • Continuous learning opportunities to grow your skills and career
  • Remote-first flexibility to work where you work best, with Ottawa, Toronto, or Calgary preferred for this role.
Fullscript shares salary ranges to support transparency and help candidates make informed decisions. The range shown reflects base salary only and does not include stock options, wellness stipends, or other benefits that are part of Fullscript's total rewards package.
 
Final compensation depends on experience, skills, and location. We review pay regularly to stay aligned with market data and internal equity. Benefits and total rewards may vary by region.

Why Fullscript

Great work happens when people feel supported, trusted, and inspired. At Fullscript, we stay curious and keep finding smarter ways to make care better. We grow together, take on new challenges, and focus on impact. We put people first, work as a team, and leave egos at the door.
 
What to Know Before You Apply
 
We're grateful for the interest in joining Fullscript. To make sure your application reaches our hiring team, please apply directly through our careers page.
A quick note: Due to the high volume of applications, we're not able to respond to phone or email inquiries about application status. If there's a match, our team will reach out directly.
 
Fullscript is an equal opportunity employer committed to creating an inclusive workplace. Accommodations are available upon request at [email protected].
 
All offers are contingent on successful background checks conducted in compliance with federal, state, and provincial laws.
 
We use AI tools to support parts of the hiring process, including screening and reviewing responses. Final hiring decisions are always made by people and follow all applicable privacy and employment laws in Canada and the U.S.
 
Learn More
 
www.fullscript.com
@fullscriptHQ on instagram
Let's make healthcare whole 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
apply for this job

Apply