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Data Analytics Engineer Jobs in Alberta (NOW HIRING)

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 ...

Collaborate with Data Engineering and IT teams to ensure analytics solutions align with data Lakehouse architecture and enterprise platforms. * Demonstrate a strong understanding of Data Lakehouse ...

Collaborate with Data Engineering and IT teams to ensure analytics solutions align with data Lakehouse architecture and enterprise platforms. * Demonstrate a strong understanding of Data Lakehouse ...

You will work directly with client stakeholders, project teams, data engineers, architects, and analytics specialists to define business requirements, map business processes, improve data quality ...

Build reliable transformation workflows that support analytics, reporting, and data science ... Work closely with software engineers, data analysts, and data scientists to understand their data ...

We provide business intelligence, data assets, data products, business metrics and data Engineering that drive and enable BI and analytics to support over 15,000 employees across diverse internal ...

We provide business intelligence, data assets, data products, business metrics and data Engineering that drive and enable BI and analytics to support over 15,000 employees across diverse internal ...

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Showing results 1-20

Data Analytics Engineer information

See Alberta salary details

$65.5K

$117.1K

$197.5K

How much do data analytics engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data analytics engineer in Alberta is $117,079.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,500.00 and $132,000.00 per year, depending on experience, location, and employer.

How do Data Analytics Engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

Can a data engineer make 200k?

Data engineers can earn $200,000 or more annually, especially with experience, advanced skills in cloud platforms, big data tools, and certifications. Salaries vary by location, industry, and company size, with senior roles and those in high-demand markets more likely to reach or exceed this level.

What engineers make $500,000?

Senior data analytics engineers with extensive experience, advanced skills in data modeling, machine learning, and proficiency with tools like Python, SQL, and cloud platforms can reach salaries of $500,000 or more, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes equity compensation.

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

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

Is 40 too late for data science?

Data Analytics Engineers and data science professionals can successfully transition into the field at age 40 or older, as skills such as programming, statistical analysis, and experience with tools like Python or SQL are valuable regardless of age. Many employers value diverse experience and lifelong learning, and certifications or online courses can help enhance credentials at any age.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and systems to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to deliver actionable insights.
What are the most commonly searched types of Data Analytics Engineer jobs in Alberta? The most popular types of Data Analytics Engineer jobs in Alberta are:
What are popular job titles related to Data Analytics Engineer jobs in Alberta? For Data Analytics Engineer jobs in Alberta, the most frequently searched job titles are:
Infographic showing various Data Analytics Engineer job openings in Alberta as of July 2026, with employment types broken down into 1% Internship, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution, with an average salary of $117,079 per year, or $56.3 per hour.

Senior Data Analytics Developer - Fabric Platform

Krux Analytics Inc.

Calgary, AB • On-site, Remote

Full-time

Re-posted 24 days ago


Job description

SENIOR DATA ANALYTICS DEVELOPER-FABRICPLATFORM

At Krux,Innovation Happens Together, by being a true partner to our customers, by valuing collaboration and teamwork, and by including a diversity of industry and life experience.


We are seekingaSenior Data Analytics Developer - Fabric Platformto join our team. Reporting to theSoftware Development Manager, youwillbe responsibleforbuilding the data infrastructure that is keyto our products by organizing, collecting, and interpreting dataand thenturning that informationinto actionable insightsthat inform company decisions and drivesgrowth.


You will be part of a team that is self-motivated,highly collaborative,eager to learn and be challenged, and enjoys having fun.


Who are we?

Krux builds innovative SAAS solutions for the mining industry. We empower our customers to make better decisions through real-time data management and analytics. Understanding our customer's needs and the ability to solve their problems is what sets us apart. Krux, founded in 2016 and headquartered in Alberta, has global reach. We support client's operations on every continent (well, except Antarctica).


What you will do

  • Design, develop andmaintainenterprise scale Power BI semantic models (tabular)
  • Architect scalable and high-performance data modelsto support multi-tenant SaaS analytics
  • Define best practices for dataset design, governance, andlifecyclemanagement
  • Optimizemodel performance, DAX calculations,aggregationsand storage strategies
  • Manage and enhance Power BI service environments (workspaces, deployment pipelines, security)
  • Monitor and improve analytical database performance in cloud environments
  • Conduct model tuning and capacity optimization to support growth and usage scaling
  • Evaluate and enhance current analytics platform architecture
  • Partner withteammates forETL and data pipeline improvements
  • Providetechnical guidance on semantic layer design and analytics best practices
  • Support cross functional stakeholders with scalable reporting architecture
  • Assistin high-priority analytics platform issues

Who you are:

  • You areanexpertinPower BIdata modeling and Power BI services
  • You are deeply performance-minded, with a strong instinct for optimization, tuning, and proactivelyidentifyingissues before theyimpactusers or systems.
  • You are security-conscious and disciplined, understanding the importance of data protection, access controls, and system reliability in production environments.
  • You are a collaborative team player who works effectively with developers, QA, and product partners to solve complex problems and improve delivery outcomes.
  • You are a mentor and continuous learner who enjoys elevating others, improving engineering practices, and staying current with evolving database technologies.

What you bring:

  • Bachelor's Degree (Computer Science, Technology, Engineering, or related field)
  • 10+years of experienceas a data analyticsdeveloperor engineer
  • 5+ years of experience in developing dataarchitecture solutions using Tabular Editoris highly desirable
  • Experience in the energy, drilling and/ormining sector is an asset
  • Experience with databases for high performance, multi-tenant web applications is necessary
  • Familiarity with Azure cloud data services
  • Experience withdevtoolsincluding Git, Azure, DevOps, Visual Studio, Jira
  • Understandingof modern data development technologies (data engineering, pipeline, ETL)
  • Strong attention to detail, critical thinking, and problem-solving skills.


Work Location:
Calgary, AB (Office islocateddowntown)

Work remotely:Hybridwork schedule


When You Work at Krux:

  • You will be valued and respected.We believe every team member brings valuable ideas and experiences no matter their seniority. We support and empower the team and trust you to get the job done.
  • You will be part of a team where we lend each other a hand.We strive for high performance by fostering an environment that emphasizes communication, collaboration, and mentorship. We believe that the only way to succeedis together.
  • You will help our customers.Not every roleis customerfacing but at the end of the day we are all working to make ourcustomers'lives easier. Our goal is to create innovative solutions with a strong emphasis on user experience.
  • You will have a life outside of work.We have partners, kids, families, and friends too, so we realize that work is just one part of your life. Krux offerswork-life balance with flexible hours anda hybrid schedule.


We value the power of our differences and at Krux, we walk our talk. We have a diverse team(including in leadership positions)and are dedicated to creating a diverse,equitable,and inclusive environment. We ensure equal opportunity for all applicants and encourage people of allvisible minorities, includingIndigenous applicants,and those of any religion, sex, age, ability, sexual orientation, genderidentityor expression to apply.

Now What?

If this position sounds like a great fit, we want to hear from you!


Submit your cover letter and resumetoday.