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Entry Level Ai Data Engineer Jobs in Calgary, AB

Interested in starting your AI & Software Development career at the intersection of AI, data, and ... You'll work closely with senior developers and engineers, product leads, and domain experts ...

They know what their data says, but not where or when things actually happen. That gap costs real ... The RoleThe Spatial AI Engineer builds the systems that let AI models, applications, and ...

... AI * Strong programming skills within one or more of these development languages - C / C++ / R / Java / Python * Good experience with Large Language Model technologies * Experience within Data ...

MongoDB is seeking a Software Engineer with solid software engineering skills and a machine ... We have redefined the data platform for the AI era, enabling builders to create, transform, and ...

Bridge Cloud, Data, and AI delivery teams by providing software engineering depth, AI application developmentexperienceand enterprise-grade cloud implementation skills. * You will respondto the ...

Systems Developer Company Overview Stream Systems (www.streamsystems.ca) is a leading-edge ... Your role is integral to the design, development, and implementation of AI/ML models into data ...

... data analysis, and explore AI-driven methods to improve algorithm tunning or improve development efficiency. You will support some of the industry's leading companies by coordinating and ...

... data analysis, and explore AI-driven methods to improve algorithm tunning or improve development efficiency. You will support some of the industry's leading companies by coordinating and ...

Associate Analog Design Engineer

Calgary, AB · On-site

CA$70K - CA$75K/yr

... data centres, 5G wireless, fibre-to-the-home networks and ultra-fast connectivity within AI ... As an Associate Analog IC Design Engineer, you will design, verify, and evaluate high-speed ...

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Entry Level Ai Data Engineer information

What is an entry level AI data engineer?

An Entry Level AI Data Engineer is a professional who helps build and maintain data pipelines and infrastructure to support artificial intelligence and machine learning applications. They typically work with large volumes of data, ensuring it is properly collected, cleaned, and organized for analysis. Their responsibilities may include working with databases, data processing tools, and cloud platforms, as well as collaborating with data scientists and software engineers to enable AI-driven solutions. This role is ideal for recent graduates or those new to the field, providing foundational experience in data engineering within the context of AI.

What are some common challenges faced by entry level AI data engineers in their first year on the job?

Entry level AI data engineers often encounter challenges such as learning to manage large datasets efficiently, understanding complex data pipelines, and adapting to rapidly evolving AI tools and frameworks. Collaborating with data scientists and senior engineers can be initially overwhelming, but it's a great opportunity to learn industry best practices. Balancing multiple tasks like data cleaning, preprocessing, and supporting model deployment while honing programming skills is typical. Proactively seeking feedback and asking questions is key to overcoming these hurdles and growing in the role.

What are the key skills and qualifications needed to thrive as an entry level AI data engineer, and why are they important?

To thrive as an Entry Level AI Data Engineer, you need proficiency in programming languages like Python or Java, a foundational understanding of data structures and algorithms, and a relevant degree in computer science or a related field. Familiarity with data processing frameworks (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure), and basic knowledge of machine learning libraries are typically expected. Strong analytical thinking, attention to detail, and effective teamwork set outstanding candidates apart. These skills and qualities are crucial for building reliable data pipelines, supporting AI models, and ensuring efficient collaboration within technical teams.

What is the difference between Entry Level Ai Data Engineer vs Data Analyst?

AspectEntry Level Ai Data EngineerData Analyst
Required SkillsBasic programming, data modeling, understanding of AI/ML conceptsData visualization, statistical analysis, SQL proficiency
CertificationsPython, SQL, entry-level AI/ML coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, AI startups, data-driven teamsBusiness, marketing, finance sectors
Job FocusBuilding AI models, data pipelines, integrating AI solutionsInterpreting data, creating reports, supporting decision-making

While both roles involve working with data, Entry Level Ai Data Engineers focus on developing AI models and data infrastructure, whereas Data Analysts primarily analyze data to generate insights. The former requires some knowledge of AI/ML, while the latter emphasizes statistical and visualization skills.

How to get into entry level AI data engineering?

To enter an entry-level AI data engineering role, develop skills in programming languages like Python and SQL, understand data pipelines and databases, and gain experience with cloud platforms such as AWS or Azure. Completing relevant certifications or courses in data engineering and machine learning can also improve job prospects.

What are the most commonly searched types of Ai Data Engineer jobs in Calgary, AB?

The most popular types of Ai Data Engineer jobs in Calgary, AB are:

What job categories do people searching Entry Level Ai Data Engineer jobs in Calgary, AB look for?

The top searched job categories for Entry Level Ai Data Engineer jobs in Calgary, AB are:

Infographic showing various Entry Level Ai Data Engineer job openings in Calgary, AB as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Senior Consultant, Databricks Data Engineer, Data & AI

Calgary, AB

Full-time

Re-posted 22 days ago


Job description

Overview

At KPMG in Canada, our people bring their unique perspectives to Canada’s most important challenges. Here, you can build momentum that reaches beyond our business, develop skills for the future, and take ownership of your career with support at every stage. Join a firm where your career can make a difference.

Are you a talented leader with a proven track record for motivating teams and delivering exceptional client service?

Our team is looking for a Data Engineer with extensive hands-on expertise in Databricks and strong consulting capability. This role will support and lead modernization initiatives from legacy/on-prem data platforms to scalable, secure, and cost-optimized Lakehouse architectures using Databricks and similar technologies.


What you will do
  • Partner with clients to understand business goals, gather requirements, and translate them into actionable technical designs and delivery plans.
  • Work with the engagement team to translate business and analytics requirements into a data strategy for the engagement including ETL/ELT, data model, and staging data for analysis.
  • Contribute to end-to-end solution architecture for repeatable, cost-optimized implementations (including non-functional requirements and operational readiness).
  • Lead delivery of modern data platforms on Databricks (ETL/ELT pipelines, workload migrations, governance enablement).
    • Implement Delta Lake / Lakehouse patterns including medallion architecture, CDC, incremental processing, and data quality controls.
    • Develop data pipelines to support streaming, incremental, batch data, etc.
    • Design and implement scalable batch and streaming pipelines using Spark and modern orchestration patterns.
    • Apply CI/CD and engineering best practices (version control, automated deployment, testing, and release management) to data engineering workflows.
    • Establish and operationalize governance using Unity Catalog, including access controls, lineage, and security frameworks.
  • Support testing and production releases, including troubleshooting, performance tuning, and stabilization.
  • Proactively contributes to the creation of presentation materials relating to data activities for stakeholder discussions.

What you bring to the role
  • University degree in computer engineering, mathematics, data science or related disciplines
  • 4+ years of professional experience in a related field like Data Engineering, Business Intelligence, or related field with a track record of manipulating, processing, and extracting value from large datasets.
  • 2+ years of hands-on experience with Databricks, including advanced features (Delta Lake, Unity Catalog) with Databricks or cloud certifications with 1-2 years of experience leading workstreams / client-facing delivery.
  • Strong proficiency in SQL and solid understanding of modern data modeling principles, dimensional modeling, and data warehousing concepts.
  • Proficiency in Python (or similar scripting languages) for data processing, automation, and analytical workflows
  • Strong experience working in teams to perform ETL (extract, transform and load) of data from a variety of databases from SQL, NoSQL, etc.
  • Proven experience leading large-scale data migrations (ETL, workloads, cloud platforms), including migration of legacy data platforms or ETL workloads to cloud-native environments.
  • Experience applying CI/CD practices to data engineering workflows, including version control, automated deployment, and pipeline orchestration.
  • Independent ability to review the data quality and data definitions and perform data cleansing and data management tasks.
  • Experience collaborating within cross-functional and multi-disciplinary teams to solve complex data challenges, including processing semi-structured and unstructured data
  • Experience in at least one major cloud service: AWS, Azure and GCP with understanding of cloud-native services, identity management, and scalable architecture principles.
  • Certifications: Databricks Certified Data Engineer (Associate or Professional) and/or relevant cloud certifications (e.g., Azure, AWS, or GCP architecture or data engineering credentials) are preferred.

KPMG Ontario Region Pay Range Information

The expected base salary range for this position is $77,000 to $102,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program.

KPMG BC Region Pay Range Information   

The expected base salary range for this position is $73,000 to $100,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program. 

Providing you with the support you need to be at your best


Our Values, The KPMG Way

Integrity, we do what is right | Excellence, we never stop learning and improving | Courage, we think and act boldly | Together, we respect each other and draw strength from our differences | For Better, we do what matters

KPMG in Canada is a proud equal opportunities employer and we are committed to creating a respectful, inclusive and barrier-free workplace that allows all of our people to reach their full potential. A diverse workforce is key to our success and we believe in bringing your whole self to work. We welcome all qualified candidates to apply and hope you will choose KPMG in Canada as your employer of choice.

Adjustments and accommodations throughout the recruitment process

At KPMG, we are committed to fostering an inclusive recruitment process where all candidates can be themselves and excel. We aim to provide a positive experience and are prepared to offer adjustments or accommodations to help you perform at your best. Adjustments (informal requests), such as extra preparation time or the option for micro breaks during interviews, and accommodations (formal requests), such as accessible communication supports or technology aids, are tailored to individual needs and role requirements. You will have an opportunity to request an adjustment or accommodation at any point throughout the recruitment process. If you require support, please contact KPMG’s Employee Relations Service team by calling 1-888-466-4778.

AI Usage

Weembrace the use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. AI tools may help with organizing applications or surfacing relevant qualifications. However, no hiring decisions are made using AI. Every hiring decision is made by our hiring managers and recruitment professionals, who are equipped with training that empowers them to use these tools responsibly. AI technologies used in our recruitment process undergo detailed risk assessments, including security and privacy requirements, that align with KPMG’s Trusted AI framework.

We believe technology should empower human judgment, not replace it. It’s one of the many ways we’re delivering on our vision of being a technology-first, people-driven firm.

Qualifications:
  • University degree in computer engineering, mathematics, data science or related disciplines
  • 4+ years of professional experience in a related field like Data Engineering, Business Intelligence, or related field with a track record of manipulating, processing, and extracting value from large datasets.
  • 2+ years of hands-on experience with Databricks, including advanced features (Delta Lake, Unity Catalog) with Databricks or cloud certifications with 1-2 years of experience leading workstreams / client-facing delivery.
  • Strong proficiency in SQL and solid understanding of modern data modeling principles, dimensional modeling, and data warehousing concepts.
  • Proficiency in Python (or similar scripting languages) for data processing, automation, and analytical workflows
  • Strong experience working in teams to perform ETL (extract, transform and load) of data from a variety of databases from SQL, NoSQL, etc.
  • Proven experience leading large-scale data migrations (ETL, workloads, cloud platforms), including migration of legacy data platforms or ETL workloads to cloud-native environments.
  • Experience applying CI/CD practices to data engineering workflows, including version control, automated deployment, and pipeline orchestration.
  • Independent ability to review the data quality and data definitions and perform data cleansing and data management tasks.
  • Experience collaborating within cross-functional and multi-disciplinary teams to solve complex data challenges, including processing semi-structured and unstructured data
  • Experience in at least one major cloud service: AWS, Azure and GCP with understanding of cloud-native services, identity management, and scalable architecture principles.
  • Certifications: Databricks Certified Data Engineer (Associate or Professional) and/or relevant cloud certifications (e.g., Azure, AWS, or GCP architecture or data engineering credentials) are preferred.

KPMG Ontario Region Pay Range Information

The expected base salary range for this position is $77,000 to $102,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program.

KPMG BC Region Pay Range Information   

The expected base salary range for this position is $73,000 to $100,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program. 

Providing you with the support you need to be at your best

Education:UNAVAILABLEEmployment Type: FULL_TIME