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Data Masking Jobs in Alberta (NOW HIRING)

Bagging of finished product in powder format, while wearing protective mask. * Carrying and pilling ... Monitor and record process data on a computer * Documentation: maintain all required documentation ...

Bagging of finished product in powder format, while wearing protective mask. * Carrying and pilling ... Monitor and record process data on a computer * Documentation: maintain all required documentation ...

Bagging of finished product in powder format, while wearing protective mask. * Carrying and pilling ... Monitor and record process data on a computer * Documentation: maintain all required documentation ...

S., and launched Titan Matrix, a new division supporting tech‑driven industries including data ... Prepare metal and other surfaces for painting, including cleaning, sanding, and masking. * Apply ...

S., and launched Titan Matrix, a new division supporting techdriven industries including data ... Prepare metal and other surfaces for painting, including cleaning, sanding, and masking. * Apply ...

Laboratory Assistant

Calgary, AB · On-site

CA$20.74/hr

Carry out all required data processing (i.e. calculations, data review, data entry, archival, etc ... Wear issued personal protective equipment (PPE) such as dust masks, gloves etc., when required;

Laboratory Assistant

Calgary, AB · On-site

CA$20.74/hr

Carry out all required data processing (i.e. calculations, data review, data entry, archival, etc ... Able to wear issued personal protective equipment (PPE) such as dust masks, gloves etc., when ...

Laboratory Analyst

Calgary, AB · On-site

CA$25.09/hr

Data entry into LIMS; * Prepare calibration and quality control standards, duplicate and spike ... Wear issued personal protective equipment (PPE) such as dust masks, gloves etc., when required;

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Data Masking information

What is data masking?

Data masking is a process used to protect sensitive information by replacing original data with fictional but realistic data. The goal is to ensure that confidential data, such as personal identification numbers or financial information, cannot be accessed by unauthorized users, especially in non-production environments like testing or development. Data masking maintains the format and structure of the original data so that applications can function correctly while ensuring privacy and compliance with regulations. This technique is commonly used in industries that handle large amounts of sensitive information, such as healthcare, finance, and government.

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

To thrive as a Data Masking Specialist, you need a solid understanding of data security principles, database management, and regulatory compliance, typically supported by a degree in computer science or information security. Familiarity with data masking tools such as Informatica, IBM Optim, or Microsoft SQL Server Data Masking, as well as relevant certifications like CISSP or CISM, is often required. Strong analytical thinking, attention to detail, and effective communication are standout soft skills in this role. These competencies are crucial to ensure sensitive data is properly protected, minimizing security risks and meeting compliance requirements.

What are some common challenges faced by professionals working in data masking roles?

Professionals in data masking roles often encounter challenges such as ensuring that masked data remains useful for development or testing while maintaining strict compliance with privacy regulations. Balancing security with data utility can be complex, especially when working with legacy systems or large-scale databases. Collaboration with database administrators, developers, and compliance teams is essential to design effective masking strategies and troubleshoot issues as they arise. Staying updated on evolving data privacy laws and best practices is also crucial for long-term success in this field.

What is the difference between Data Masking vs Data Analyst?

AspectData MaskingData Analyst
Required CredentialsTypically no formal certifications, but knowledge of data security and privacy standardsBachelor's degree in data science, statistics, or related field; certifications like CAP or Microsoft Certified Data Analyst are common
Work EnvironmentIT/security teams, often within data security or compliance departmentsBusiness intelligence, analytics teams, or data departments across various industries
Employer & Industry UsageUsed in industries handling sensitive data like finance, healthcare, and retailUsed across industries for data-driven decision making, reporting, and insights

Data Masking focuses on protecting sensitive information by obfuscating data to ensure privacy and security. Data Analysts interpret and analyze data to generate insights. While Data Masking is a technical security process, Data Analysts work with the data post-masking to support business decisions.

What are popular job titles related to Data Masking jobs in Alberta?

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

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

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

Infographic showing various Data Masking job openings in Alberta as of August 2026, with employment types broken down into 53% Full Time, 40% Contract, and 7% Nights. Highlights an 94% In-person, and 6% Remote job distribution.

Data Engineer - Intermediate (REMOTE) JP975

P@thlion Staffing Careers

Edmonton, AB • Remote

Full-time

Posted 28 days ago


Job description

Project Name:

Digital Regulatory Assurance System

Scope:

Modernization initiatives across the Government of Alberta are fundamentally changing how ministry users collect, manage, analyze, and use data as legacy systems are transformed into modern Data Management and Geospatial Platforms. This shift requires dedicated analytical capacity to ensure that the value of modernized data assets is fully realized.

DRAS is a Government of Alberta regulatory transformation initiative led by Environment and Protected Areas (EPA) to modernize, digitize, and streamline environmental and natural resource regulatory processes. DRAS supports the full regulatory lifecycle, from application and authorization to monitoring, compliance, remediation, and closure through a single, consolidated digital platform

As DRAS development continues, the volume, variety, and complexity of structured data continue to grow, creating a sustained need for dedicated data engineering and data product expertise. The Data Product Analyst role is critical to ensuring that modernization delivers tangible business value. This role will design, build, and operate reliable data pipelines that ingest and integrate data into the DMP, apply standardized transformations, enforce data quality and governance controls, and produce trusted, analytics‑ready datasets that support regulatory oversight, compliance monitoring, and evidence‑based decision‑making aligned with DRAS objectives.

This position will primarily support the Digital Regulatory Assurance System (DRAS) program, where high quality, timely analytics are essential to regulatory and compliance functions. As data and analytics maturity increases, the role may be expanded to support additional enterprise data initiatives.

Duties:

  • Design and implement scalable, secure, and high-performance data architecture on Microsoft Azure, supporting both cloud-native and hybrid environments.
  • Lead the development of data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
  • Work with the Data Architect and manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2, ensuring efficient access and governance.
  • Integrate data from diverse source systems including ServiceNow, and geospatial systems, using APIs, connectors, and custom scripts.
  • Develop and maintain robust data models and semantic layers to support operational reporting, analytics, and machine learning use cases.
  • Build and optimize data workflows using Python and SQL for data cleansing, enrichment, and advanced analytics within Azure Databricks.
  • Design and expose secure data services and APIs using Azure API Management for downstream systems.
  • Implement data governance practices, including metadata management, data classification, and lineage tracking.
  • Ensure compliance with privacy and regulatory standards (e.g., FOIP, GDPR) through role-based access controls, encryption, and data masking.
  • Monitor and troubleshoot data pipelines and integrations, ensuring reliability, scalability, and performance across the platform.
  • Utilize AI and automation tools to streamline data engineering workflows, including pipeline development, testing, monitoring, and documentation.
  • Leverage AI-assisted tools for code generation, optimization, and review to improve development efficiency and code quality.
  • Design and curate standardized, high‑quality datasets that are suitable for advanced analytics and future AI use cases.
  • Other duties as needed