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Data Processor Jobs in Alberta (NOW HIRING)

ShyftLabs

Data Engineer

Calgary, AB

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 ...

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All JobsData Processor JobsData Processor Jobs in Alberta

Data Processor information

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$8

$16

$27

How much do data processor jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for data processor in Alberta is $16.67, according to ZipRecruiter salary data. Most workers in this role earn between $13.46 and $18.75 per hour, depending on experience, location, and employer.

What is a data processor?

A data processor transfers, organizes, and processes personal data for a company. It is typically an entry-level job that serves as a starting point for a career as a data controller. As a data processor, your duties involve processing incoming documents, transferring analog documents into digital data, verifying the information in all documents, updating document formats, and creating detailed reports on company data use and management. Qualifications for this career include excellent computer skills and a bachelor’s degree in computer science or data management.

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

To thrive as a Data Processor, you need strong attention to detail, accuracy in data entry, and a high school diploma or equivalent. Familiarity with spreadsheet software (such as Microsoft Excel), database management systems, and sometimes data processing software is typically required. Excellent organizational skills, the ability to follow procedures, and effective time management make someone stand out in this role. These skills ensure data integrity, minimize errors, and support efficient information management within an organization.

What are some common challenges faced by data processors and how can they be addressed?

Data Processors often encounter challenges such as managing large volumes of data accurately and efficiently, dealing with inconsistent or incomplete data, and ensuring data privacy and compliance. To address these, it's important to develop strong attention to detail, become proficient with data processing software, and stay updated on relevant data protection regulations. Collaborating closely with data analysts and IT teams can also help resolve data issues and improve workflow efficiency.

What is the difference between Data Processor vs Data Entry Clerk?

AspectData ProcessorData Entry Clerk
Required CredentialsHigh school diploma; some roles may require basic certificationsHigh school diploma; no specialized certifications typically needed
Work EnvironmentOffice settings, data centers, or remote workOffice environments, often in administrative settings
Employer & Industry UsageBusinesses, government agencies, financial institutionsCorporations, healthcare, retail, administrative offices
Common Search & ComparisonOften compared for data handling and processing tasksCompared for data input and administrative support roles

While both roles involve handling data, Data Processors typically perform more complex data management and validation tasks, often requiring some technical skills. Data Entry Clerks focus on inputting data accurately and efficiently. Understanding these differences helps in choosing the right role based on skills and career goals.

How much does a data processor earn?

The average salary for a data processor typically ranges from $30,000 to $45,000 per year, depending on experience, location, and industry. Entry-level positions may start lower, while experienced data processors with specialized skills or certifications can earn higher wages. Many roles also offer benefits such as health insurance and paid time off.

What do you do as a data processor?

A data processor collects, organizes, and manages data to ensure accuracy and consistency. They often use software tools like spreadsheets or databases and may perform tasks such as data entry, validation, and updating records to support business operations.
More about Data Processor jobs

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For Data Processor jobs in Alberta, the most frequently searched job titles are:

What job categories do people searching Data Processor jobs in Alberta look for?

The top searched job categories for Data Processor jobs in Alberta are:

What are popular job titles related to Data Processor jobs in AB?

For Data Processor jobs in AB, the most frequently searched job titles are:

Data Processor jobs near you
Infographic showing various Data Processor job openings in Alberta as of August 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 68% In-person, 16% Hybrid, and 16% Remote job distribution, with an average salary of $34,669 per year, or $16.7 per hour.

Senior Data Engineer - Oil & Gas

Data Elephant Inc

Calgary, AB • On-site

Contractor

Re-posted 19 days ago

Job description

We are looking for a Senior AI/ML Engineers to join our team, that sit at the intersection of software engineering, data engineering, and applied AI.



This role is ideal for someone who enjoys building end-to-end solutions - from data pipelines and backend systems to AI-powered applications - and wants to work on real-world industrial use cases that comes from an Engineering background, and has experience in Oil & Gas.


In this position, you'll contribute to a variety of impactful client projects, including:


  • Building AI-powered anomaly detection systems for operational and industrial data
  • Modernizing asset management workflows
  • Developing natural language interfaces for querying enterprise and operational data
  • Designing and implementing AI agents and copilots for business users
  • Creating scalable data pipelines and ML workflows in cloud environments
  • Enabling real-time and batch data processing for analytics and AI use cases
  • Working through complex and challenging data conditions, including incremental processing, late-arriving or changing records, complex business and engineering rules, and reconciliation of results across processing runs


The ideal candidate combines strong data engineering experience with an engineering or applied-science background. Direct experience industrial time-series data, scientific measurements, telemetry, financial reconciliation, or other datasets where accuracy, traceability, and incremental recalculation are critical.


Key Responsibilities


  • Design, build, and optimize pipelines for sensor and related operational data.
  • Develop complex transformation and calculation logic based on engineering requirements.
  • Implement robust incremental-processing patterns for high-volume and continuously changing datasets.
  • Design, build, and deploy end-to-end AI/ML solutions in production environments
  • Develop robust backend systems and APIs to support AI-driven applications
  • Build and maintain data pipelines and feature engineering workflows
  • Implement and operationalize machine learning models (training, deployment, monitoring)
  • Work with modern AI tooling (LLMs, agents, orchestration frameworks)
  • Collaborate with clients to translate business problems into technical solutions
  • Contribute to architecture decisions and best practices across projects
  • Mentor client team members and contribute to internal capability building
  • Work directly with engineering and operational SMEs to understand physical processes and translate their knowledge into technical requirements.
  • Make engineering calculations and data transformations explainable, traceable, testable, and auditable.
  • Document data lineage, calculation logic, assumptions, dependencies, and exception-handling rules.


Ideal Background

  • Senior-level experience designing and developing production data pipelines with Azure Databricks including strong experience with complex SQL, Python, Spark, or comparable data-processing technologies.
  • Demonstrated experience with incremental processing, change detection, reconciliation, and idempotent pipeline design.
  • Experience handling time-series, telemetry, sensor, operational, scientific, or industrial data.
  • Ability to work through ambiguous requirements with highly specialized SMEs.
  • Strong analytical and investigative skills, with the patience to work through detailed logic and difficult data-quality problems.
  • Degree or professional background in petroleum, reservoir, chemical, mechanical, geological, geophysical, or another relevant engineering or applied-science discipline is strongly preferred.
  • Experience in upstream oil and gas, thermal operations, SAGD, well surveillance, production engineering, or subsurface data would be a significant asset.
  • Hands-on experience with AI/ML workflows and model deployment.
  • Modern developer tooling (Cursor, AI-assisted development, Langraph, "vibe coding").



    This role presents an exciting opportunity to work on practical, high-impact AI use cases - not just prototypes, shape how AI is applied to client environments, and change the game on traditional processes and platforms.Come join a growing organization helping clients take a new, lean and value-driven approach to data and engineering!

    Apply