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Data Engineering Jobs in Alberta (NOW HIRING)

Takeaway

Senior Manager - Data Engineering

Calgary, AB · On-site +1

CA$120K - CA$160K/yr

As Senior Manager, Data Engineering, you'll lead a team of data and analytics engineers, plus a contractor pod, building the platforms and consumption layer that power decisions, ML and customer ...

Enfinite

Data Engineer, Digital Systems

Calgary, AB · Hybrid

A bachelor's degree in computer science, data engineering, electrical engineering, or a related field. * At least three years of hands-on data engineering experience. * Strong Python skills ...

TELUS

L3 Data Management (GCP)

Calgary, AB · On-site +1

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 ...

TELUS

L3 Data Management (GCP)

Edmonton, AB · On-site +1

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 ...

Data Elephant Inc

Databricks Engineer

Calgary, AB · On-site

You will work directly with client data and analytics teams, helping them migrate, modernize, and scale their data workloads while applying best practices in data engineering, security, and ...

ShyftLabs

Data Engineer

Calgary, AB

Degree in Computer Science, Engineering, Mathematics, or related STEM discipline . * Strong ... Strong understanding of data warehousing and dimensional modeling methodologies . * Hands-on ...

Blend360

AI and Data Engineer

Edmonton, AB · On-site

This role sits at the intersection of software engineering, data engineering and applied AI: you will design the pipelines that power the personas and , the models and the platform deployments that ...

TELUS

Engineering Manager - Data Ingestion

Calgary, AB · Remote

Design and own the SRE function for Level 1 data ingestion across all GCP deployments: alert policy design, SLO definition, incident management, and on-call operations * Eliminate manual data quality ...

TELUS

Engineering Manager - Data Ingestion

Edmonton, AB · Remote

Design and own the SRE function for Level 1 data ingestion across all GCP deployments: alert policy design, SLO definition, incident management, and on-call operations * Eliminate manual data quality ...

Finning

Data Engineer II

Edmonton, AB · Hybrid

Data is deeply embedded in the product, engineering, analytics, and operational culture at Finning. Finning Canada is looking to hire a permanent, fulltime Data Engineer II based either in Surrey ...

Finning

Data Engineer II

Calgary, AB · Hybrid

Data is deeply embedded in the product, engineering, analytics, and operational culture at Finning. Finning Canada is looking to hire a permanent, fulltime Data Engineer II based either in Surrey ...

Lantern

Data Architect

Edmonton, AB · On-site

Provide strategic guidance on leveraging Microsoft Data Platform technologies (such as Fabric, Azure Synapse, Power BI, etc.) for data warehousing, data engineering, semantic modeling, analytics ...

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Showing results 1-20

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Data Engineering information

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their expertise in tools like SQL, Spark, and cloud platforms remains critical for managing data workflows and ensuring data quality.

What work does a data engineer do?

A data engineer designs, builds, and maintains data pipelines and infrastructure 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 optimized for analysis by data scientists and analysts.

What are the typical daily responsibilities of a Data Engineer?

Data Engineers regularly design, build, and maintain scalable data pipelines to support analytics and business intelligence teams. Their daily tasks often involve working with large datasets, optimizing data storage, ensuring data integrity, and troubleshooting data-related issues. Collaboration with data scientists, analysts, and software engineers is common to align on data requirements and improve workflows. You may also participate in regular code reviews and contribute to the ongoing improvement of data infrastructure. This role is ideal for problem-solvers who enjoy working with both code and complex systems in a collaborative, fast-paced environment.

What engineers make 500,000?

Senior data engineers with extensive experience, specialized skills in cloud platforms, and advanced knowledge of data architecture can earn salaries approaching or exceeding $500,000 annually, 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 stock options or bonuses.

What is a Data Engineering job?

A Data Engineering job involves designing, building, and maintaining the infrastructure that enables efficient data collection, storage, and processing. Data Engineers develop pipelines to transform raw data into usable formats for analytics and machine learning. They work with databases, big data technologies, and cloud platforms to ensure data is accessible and reliable. Their role is crucial for organizations to make data-driven decisions and optimize business processes.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. They typically require skills in SQL, cloud platforms, and data pipeline tools like Apache Spark or Kafka, making their expertise valuable across many industries. The role is expected to remain strong as organizations continue to prioritize data infrastructure and analytics capabilities.

What are the key skills and qualifications needed to thrive in the Data Engineering position, and why are they important?

To thrive in Data Engineering, you need a solid background in programming (such as Python, Java, or Scala), data modeling, and database management, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms like AWS or Azure, big data frameworks (e.g., Hadoop, Spark), and relevant certifications is highly valued. Strong problem-solving abilities, effective communication, and the ability to work collaboratively across teams are key soft skills for this role. These attributes are crucial for designing robust data pipelines, ensuring data quality, and enabling organizations to make data-driven decisions efficiently.

What are the most commonly searched types of Data Engineering jobs in Alberta? The most popular types of Data Engineering jobs in Alberta are:
What are popular job titles related to Data Engineering jobs in Alberta? For Data Engineering jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Data Engineering jobs in Alberta look for? The top searched job categories for Data Engineering jobs in Alberta are:
Data Engineering jobs near you
Infographic showing various Data Engineering 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 Engineering - Data Ingestion & Infrastructure

Data Engineering - Data Ingestion & Infrastructure

TELUS

Calgary, AB

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

Join our team and what we'll accomplish together

Data Foundation is the managed ingestion service for TELUS - the team that gets data into the platform, keeps it flowing, and guarantees its quality before anyone downstream feels a problem. We operate multiple deployments across TELUS, Health, Digital, and Agriculture under one operating model, and we own everything from source to trusted raw data.

In this role, you will design, develop, and support data pipelines and the platform they run on. You'll build ingestion flows, contribute to the onboarding tooling every team at TELUS uses to bring data into the platform, and play an active role in the SRE practice that keeps everything running. You'll work across greenfield deployments, legacy system migrations, and the standards that define how data moves across TELUS.

You'll also mentor junior team members and lead resolution of critical operational issues. This is a role for someone who takes ownership and brings others along.

What you will do

Pipeline & Ingestion Engineering

  • Design and build data extraction, ingestion, and pipeline flows across deployments (TELUS, Health, Digital, Agriculture), both cloud and on-prem where applicable
  • Implement data contracts at the ingestion layer ensuring data arrives, flows on schedule, and meets quality standards before it becomes available as raw data
  • Contribute to the inner-source codebase; participate in solution reviews and code reviews for pipelines contributed by Health, Digital, and other teams

Site Reliability & Data Quality

  • Develop test strategies and site reliability engineering measures for data pipelines and solutions, build automated assurance in, not manual checks after
  • Lead resolution of critical operations issues including post-implementation reviews and blameless post-mortems
    Participate in on-call rotation 

Onboarding Tooling & Standards

  • Build and maintain the self-serve onboarding tooling that source teams and business units use to bring new data sources into the platform
  • Perform application impact assessments, requirements reviews, and develop work estimates for onboarding requests
  • Contribute to the onboarding standard, ensuring it stays consistent and usable across all deployments

Platform & Infrastructure

  • Apply working knowledge of infrastructure-as-code to contribute to the shared GKE cluster and deployment pipelines
  • Participate in agile development scrums and solution reviews
  • Mentor L1 and L2 Data Engineering Specialists on the team
What you bring
  • 4+ years of data engineering experience
  • 2+ years working on data solution architecture and design
  • Intermediate proficiency in Python or Java, including pipeline development
  • SQL and database proficiency
  • Familiarity with quality assurance and site reliability engineering practices for data solutions
  • Working knowledge of infrastructure-as-code (Terraform, Ansible, Pulumi, or equivalent)
  • Data modeling experience
  • Bachelor's degree in Software Engineering, Computer Science, Mathematics, or a related field (or equivalent experience)

Great-to-haves

  • Data Engineering certification
  • Experience with Kafka or streaming data movement patterns
  • GCP and BigQuery experience
  • Familiarity with Kubernetes/GKE
  • Background in a regulated industry (healthcare, telecommunications) or compliance-driven data environments
  • Experience contributing to or maintaining a shared internal platform used by multiple teams

What TELUS employees say

Pay

Hours and flexibility

Workplace

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