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Data Engineer Data Jobs in Calgary, AB (NOW HIRING)

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 ...

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 ...

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 ...

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 ...

Join us as a Specialist Mine Engineer, Data Analytics, and help transform complex operational data into insights that improve performance, efficiency, and decision-making across oil sands mining. In ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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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Data Engineer Data information

What are some common challenges Data Engineers face when integrating data from multiple sources?

Data Engineers often encounter challenges such as inconsistent data formats, varying data quality, and differing update frequencies when integrating data from multiple sources. Ensuring data integrity and designing robust ETL pipelines that can handle these discrepancies is a key part of the role. Collaboration with data analysts, database administrators, and source system owners is crucial to resolve data mapping issues, automate data validation, and maintain reliable data flows within the organization.

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

AspectData Engineer DataData Analyst
Primary RoleBuilds and maintains data pipelines and infrastructureAnalyzes data to generate insights and reports
Skills & CertificationsSQL, Python, ETL tools, cloud platformsSQL, Excel, data visualization tools
Work EnvironmentData engineering teams, IT departmentsBusiness units, analytics teams
Industry UsageTech, finance, healthcare, any data-driven industryMarketing, finance, operations, business intelligence

While Data Engineer Data focuses on creating and managing data infrastructure, Data Analysts interpret this data to support decision-making. Both roles require strong SQL skills, but Data Engineers typically work more with data pipelines and cloud platforms, whereas Data Analysts focus on data visualization and reporting.

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 solid understanding of data modeling, SQL, and programming languages such as Python or Java, often backed by a degree in computer science, engineering, or a related field. Familiarity with data warehousing solutions (like Amazon Redshift or Snowflake), ETL tools, and cloud platforms (such as AWS, Azure, or Google Cloud) is typically required, along with relevant certifications. Strong problem-solving abilities, collaboration, and clear communication are vital soft skills for integrating complex data systems and working with cross-functional teams. These skills ensure that data pipelines are reliable, scalable, and effectively support business intelligence and analytics needs.

What are Data Engineers?

Data Engineers are professionals who design, build, and maintain the systems and infrastructure that allow organizations to collect, store, and analyze large amounts of data. They create data pipelines, ensure data quality, and optimize data flow between systems, making it accessible for data scientists and analysts. Data Engineers often work with technologies like SQL, Python, Hadoop, and cloud platforms, and play a crucial role in supporting data-driven decision-making within organizations.

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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