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Data Engineer Jobs in Calgary, AB (NOW HIRING)

ShyftLabs

Data Engineer

Calgary, AB

Position Overview We are looking for an experienced and versatile Data Engineer to join our dynamic and fast-growing team. If you are passionate about data, solving complex problems, and working ...

360training

Data Engineer (Canada)

Calgary, AB · Remote

Data Engineer We are seeking an experienced and skilled Data Engineer to join our innovative and fast-paced team. This role is vital in designing, developing, and optimizing complex data ...

Targeted Talent

Senior Data Engineer

Calgary, AB · Remote

We are looking for an experienced Senior Data Engineer for our client. This is a permanent position that is completely remote! Our client is a global enterprise company with a product that you've ...

Targeted Talent

Senior Data Engineer

Calgary, AB · Remote

We are looking for an experienced Senior Data Engineer for our client. This is a permanent position that is completely remote! Our client is a global enterprise company with a product that you've ...

Targeted Talent

Junior Data Engineer

Calgary, AB

We are looking for an experienced Junior Data Engineer for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

United Airlines

Senior Data Engineer

Calgary, AB

CA$76K - CA$176K/yr

Job Summary We are seeking an experienced Data Engineer with strong expertise in Databricks, Apache Airflow, Python, and PySpark to design, build, and maintain scalable, high-performance data ...

Targeted Talent

Junior Data Engineer

Calgary, AB

We are looking for an experienced Junior Data Engineer for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global ...

Fullscript

Senior Data Engineer

Calgary, AB · Remote

CA$11K - CA$140K/yr

As the Senior Data Engineer, you'll be part of a small team that turns messy practitioner and clinical data into reliable, analysis-ready assets that enable causal outcome modeling, lab normalization ...

Syndio

Staff Data Engineer

Calgary, AB

About the Role We're looking for a Staff Data Engineer to define the architecture and long-term evolution of Syndio's data platform as we scale into AI-driven products. This role owns the technical ...

Syndio

Staff Data Engineer

Calgary, AB · Remote

CA$180/hr

About the Role We're looking for a Staff Data Engineer to define the architecture and long-term evolution of Syndio's data platform as we scale into AI-driven products. This role owns the technical ...

Miratech

Senior Data Engineer

Calgary, AB · On-site +1

The Senior Data Engineer is responsible for designing, developing, and supporting databases that power a large-scale IVR and contact center platform. The role is focused on backend database ...

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Showing results 1-20

All JobsData Engineer JobsData Engineer Jobs in Calgary, AB

Data Engineer information

See Calgary, AB salary details

$60K

$122.6K

$181K

How much do data engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for data engineer in Calgary, AB is $122,622.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $142,500.00 per year, depending on experience, location, and employer.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

Are data engineers highly paid?

Data engineers are generally well-paid due to their specialized skills in designing and maintaining data infrastructure, with salaries often higher than many other IT roles. Compensation varies based on experience, location, and industry, but strong technical skills in programming, databases, and cloud platforms typically lead to higher earnings.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipeline tools. Entry-level data engineering positions may be available for candidates with relevant internships or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect some prior experience. Certifications or coursework in data management can also be beneficial for those starting out.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and leadership roles can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of expertise and a strong track record in data architecture and engineering.
More about Data Engineer jobs
What are the most commonly searched types of Data Engineer jobs in Calgary, AB? The most popular types of Data Engineer jobs in Calgary, AB are:
What are popular job titles related to Data Engineer jobs in Calgary, AB? For Data Engineer jobs in Calgary, AB, the most frequently searched job titles are:
What job categories do people searching Data Engineer jobs in Calgary, AB look for? The top searched job categories for Data Engineer jobs in Calgary, AB are:
What cities near Calgary, AB are hiring for Data Engineer jobs? Cities near Calgary, AB with the most Data Engineer job openings:
Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Calgary, AB as of June 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $122,622 per year, or $59 per hour.

Data Engineer

ShyftLabs

Calgary, AB

Full-time

Medical, Dental, Vision

Posted 5 days ago

Job description

Position Overview

We are looking for an experienced and versatile Data Engineer to join our dynamic and fast-growing team. If you are passionate about data, solving complex problems, and working directly with enterprise stakeholders to translate business needs into scalable technical solutions, this role could be the perfect fit.

ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses across various industries by focusing on creating value through innovation.

In addition to strong technical expertise, we are seeking someone with strong business awareness and the ability to lead client and stakeholder communication. The ideal candidate will be comfortable collaborating with enterprise-level clients, translating complex technical concepts into business outcomes, and ensuring alignment between engineering execution and strategic objectives.

Job Responsibilities

  • Design, build, and maintain scalable and reliable batch and real-time ETL/ELT data pipelines using cloud services such as GCP Dataflow, Cloud Functions, Pub/Sub, and Cloud Composer.

  • Architect and implement robust data infrastructure capable of handling high-volume data ingestion and processing.

  • Develop and manage our central data warehouse in Google BigQuery.

  • Design and implement data models, schemas, and table structures optimized for performance, scalability, and long-term maintainability.

  • Write clean, efficient, and maintainable SQL and Python code to transform raw data into curated, analysis-ready datasets.

  • Build reliable transformation workflows that support analytics, reporting, and data science initiatives.

  • Monitor, troubleshoot, and optimize data infrastructure to ensure high performance, reliability, and cost efficiency.

  • Implement BigQuery best practices, including partitioning, clustering, query optimization, and materialized views.

  • Build and maintain curated data models that serve as the "source of truth" for business intelligence and reporting.

  • Ensure data is optimized and readily accessible for BI tools such as Looker and other analytics platforms.

  • Implement automated data quality checks, validation rules, and monitoring frameworks to ensure the integrity and reliability of data pipelines and warehouse systems.

  • Establish processes for data governance, observability, and lineage tracking.

  • Work closely with software engineers, data analysts, and data scientists to understand their data requirements and provide the necessary infrastructure and data products.

  • Lead and support client and stakeholder communication, working with enterprise clients to translate business needs into scalable data solutions.

  • Partner with product teams and leadership to ensure that technical data solutions align with business strategy and client expectations.

  • Take ownership of data platforms and architecture decisions, helping shape the future direction of our analytics and data infrastructure.

  • Identify opportunities to improve data reliability, automate workflows, and generate new insights through data.

  • Contribute to a collaborative, high-performing engineering culture with strong communication and teamwork.

Basic Qualifications

  • 5+ years of hands-on experience in data engineering, data integration, or data platform development.

  • Degree in Computer Science, Engineering, Mathematics, or related STEM discipline.

  • Strong programming and query skills in SQL and Python.

  • Experience working with distributed version control systems such as Git in an Agile/Scrum environment.

  • Experience designing and orchestrating ETL pipelines, particularly with Databricks.

  • Experience working within cloud environments (GCP, AWS, or Azure).

  • Experience with database systems such as MongoDB and Elasticsearch.

  • Strong understanding of data warehousing and dimensional modeling methodologies.

  • Hands-on experience with Airflow and Hadoop.

  • Experience using Docker for containerized workflows and reproducible environments.

  • Ability to identify opportunities to improve data quality, reliability, and automation.

  • Strong business awareness and communication skills, with the ability to collaborate with both technical teams and business stakeholders.

  • Experience within the retail industry is a plus.

Preferred Qualifications

  • Master's degree in Computer Science, Engineering, or related discipline.

  • Experience working with enterprise-scale data platforms and Fortune 500 clients.

  • Familiarity with Druid and its Python API, including Kafka integrations.

  • Strong experience using Apache Spark for large-scale data processing.

  • Experience designing real-time streaming data architectures.

  • Experience working with AI-driven platforms, data infrastructure supporting AI/ML systems, or agentic AI workflows

Why You'll Love Working at ShyftLabs
 
At ShyftLabs, your work matters. We're a growing data product company making a big impact with Fortune 500 clients and as we scale, you'll have the chance to shape solutions, influence strategy, and grow your career alongside us.
 
Here's what you can expect when you join our team:
-Work Arrangement: This role is currently fully remote, providing flexibility to work from home. As the team and organization continue to grow, there may be an opportunity for the role to transition into a hybrid work model in the future, with occasional in-office collaboration.
-Comprehensive Benefits: We cover 100% of health, dental, and vision insurance premiums for you and your dependents which means no out-of-pocket costs. Eligibility starts from day one itself.
-Growth & Learning: Access extensive learning and development resources to keep leveling up your skills.
 
Inclusion at ShyftLabs
 
We're building something big, and we want you on the journey with us. If you're ready to use data and innovation to make an impact, apply today and let's grow together.
 
ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse, and inclusive environment. We encourage applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, and nationality to apply. If you require accommodation during the interview process, let us know and we'll be happy to support you.
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