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Data Engineer Data Analyst Jobs in Alberta (NOW HIRING)

ShyftLabs

Data Engineer

Calgary, AB · On-site

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 ...

Bird Construction

Senior Data Analyst

Edmonton, AB · Hybrid

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 ...

Bird Construction

Senior Data Analyst

Calgary, AB · Hybrid

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 ...

Alquemy

Data Analyst

Edmonton, AB

Data Analyst Position Overview We are seeking a Data Analyst to support enterprise data governance, reporting, and analytics by building reliable datasets, improving data quality, and developing ...

10 Percent Recruiting Ltd.

Data Engineer

Edmonton, AB · Hybrid

Work with Business Analysts and Developers to ensure the warehouse contains the appropriate data models to handle both analytical and system reporting needs. Ensure that data security and access to ...

360training

Data Engineer (Canada)

Calgary, AB · Remote

Data Engineer We are seeking an experienced and skilled Data Engineer to join our innovative and ... Strong analytical and problem-solving skills, with a passion for continuous learning and innovation.

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 ...

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 ...

Syndio

Staff Data Engineer

Calgary, AB · Remote

CA$180/hr

Build pipelines that support both batch analytics and the event-driven data flows behind AI ... Deep experience in data engineering, data platform, or distributed systems roles * Proven track ...

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

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 ...

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All JobsData Engineer Data Analyst JobsData Engineer Data Analyst Jobs in Alberta

Data Engineer Data Analyst information

What engineers make $500,000?

Senior data engineers with extensive experience, advanced skills in cloud platforms, big data tools, and strong programming knowledge can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires specialized expertise, leadership roles, and sometimes stock options or bonuses.

How do Data Engineer Data Analysts typically collaborate with data scientists and business stakeholders?

Data Engineer Data Analysts play a crucial role in bridging the technical and analytical needs of an organization. They work closely with data scientists by preparing, cleaning, and structuring large datasets to enable advanced analytics and modeling. Additionally, they collaborate with business stakeholders to understand data requirements, translate business questions into technical solutions, and deliver actionable insights. Effective communication and teamwork are essential, as the role often involves facilitating data access, ensuring data quality, and aligning data projects with business objectives.

Is a data engineer the same as a data analyst?

A data engineer designs, builds, and maintains data pipelines and infrastructure, focusing on data collection and storage. A data analyst interprets and analyzes data to generate insights and reports. While both roles work with data, they have different skill sets and responsibilities, often requiring knowledge of tools like SQL, Python, or cloud platforms.

What pays more, a data engineer or a data analyst?

Data engineers typically earn higher salaries than data analysts due to their advanced skills in building data pipelines, working with big data tools, and managing infrastructure. While salaries vary by experience and location, data engineering roles often require knowledge of programming languages like Python or Java and cloud platforms, which contribute to higher compensation.

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

To thrive as a Data Engineer/Data Analyst, you need strong analytical and statistical skills, proficiency in programming languages like Python or SQL, and typically a degree in computer science, statistics, or a related field. Familiarity with data warehousing tools, ETL processes, and experience with platforms like Hadoop, Spark, or Tableau is often required. Attention to detail, problem-solving ability, and effective communication are crucial soft skills for interpreting data and sharing insights with stakeholders. These competencies ensure accurate data management, insightful analysis, and support data-driven decision-making within organizations.

What does a data engineer analyst do?

A data engineer analyst designs, builds, and maintains data pipelines and infrastructure to collect, store, and process large datasets. They work with tools like SQL, Python, and cloud platforms to ensure data quality and accessibility for analysis, often collaborating with data scientists and business teams.

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

AspectData EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; often certifications in cloud or data toolsBachelor's or higher in CS, Statistics, or related; often advanced degrees
Work EnvironmentBuilds data pipelines, manages databases, ensures data flowAnalyzes data, creates models, interprets insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceResearch firms, tech, finance, marketing

Data Engineers focus on developing and maintaining data infrastructure, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but Data Engineers are more involved in data architecture, whereas Data Scientists focus on modeling and analysis.

What are popular job titles related to Data Engineer Data Analyst jobs in Alberta? For Data Engineer Data Analyst jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Data Engineer Data Analyst jobs in Alberta look for? The top searched job categories for Data Engineer Data Analyst jobs in Alberta are:
What cities in Alberta are hiring for Data Engineer Data Analyst jobs? Cities in Alberta with the most Data Engineer Data Analyst job openings:
Data Engineer Data Analyst jobs near you
Infographic showing various Data Engineer Data Analyst job openings in Alberta as of July 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 67% In-person, 13% Hybrid, and 20% Remote job distribution.

Data Engineer

ShyftLabs

Calgary, AB • On-site

Full-time

Medical, Dental, Vision

Re-posted 4 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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