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Data Masking Jobs in Ontario (NOW HIRING)

Practical understanding of data security fundamentals -- RBAC, encryption (at rest/in transit), data masking, and privacy best practices. * Strong communication and cross-functional collaboration ...

RBAC, row-level and column-level security policies, data masking policies, and network policiesBuild incremental pipelines using Snowflake-native Streams, Tasks, and Dynamic Tables, keeping logic ...

OAuth2/OIDC, data masking/tokenization, PII handling, and regulatory awareness in financial services or AML. * Regulated domains: Prior experience in financial services or other highly regulated ...

... masking, encryption, and access controls for sensitive and regulated data Monitor system performance, scalability, and operational health of data quality and governance solutions Data Governance ...

You will define the end-to-end data platform (ingestion, storage, modeling, governance, quality ... Solid grasp of security and privacy controls (RBAC, encryption, tokenization/masking), and ...

You will define the end-to-end data platform (ingestion, storage, modeling, governance, quality ... Solid grasp of security and privacy controls (RBAC, encryption, tokenization/masking), and ...

Design analog/mixed-signal (AMS) circuits used in control loops, such as data converters ... Drive block-level floorplan, mask design views, and their reviews * Run post-layout and mixed ...

Anaesthesia Assistant

Sudbury, ON · On-site

CA$51.61 - CA$60.72/hr

... Provide diagnostic data to the Anaesthetist or Surgeon (e.g. blood gases, pulse oximetry ... mask ventilation, aspirate secretions from trachea and pharynx, removal of laryngeal mask airways ...

Anaesthesia Assistant

Sudbury, ON · On-site

CA$51.61 - CA$60.72/hr

... Provide diagnostic data to the Anaesthetist or Surgeon (e.g. blood gases, pulse oximetry ... mask ventilation, aspirate secretions from trachea and pharynx, removal of laryngeal mask airways ...

... perform inventory data entry · May create receiving documentation · May create shipping ... Increased cleaning protocols have been been implemented and hand sanitizer along with masks are ...

Ensure data privacy during integrations using masking and/or other anonymization/aggregation technology * Ensure data security during integrations using the most secure authentication and encryption ...

Understanding of data governance (catalog, lineage, security, RBAC, masking, compliance requirements like GDPR/CCPA). Analytics, BI, and data science Ability to design and explain analytics solutions ...

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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 Ontario?

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

Infographic showing various Data Masking job openings in Ontario as of August 2026, with employment types broken down into 52% Full Time, 41% Contract, and 7% Nights. Highlights an 94% In-person, and 6% Remote job distribution.

Part Time - Data Architect

Architech

Toronto, ON

Part-time

Re-posted 5 days ago


Job description

Build the data foundation that makes enterprise AI possible. Design secure, scalable platforms across Fabric, Azure and Databricks that make data ready for analytics and AI.

Join Us in Building the Future
At Architech, we don’t just ship software. We partner with North America’s leading brands to modernize legacy platforms, embed AI into real operations, and launch digital products that transform business outcomes. Our engineers and designers harness cloud-native tools, autonomous agents, data-driven insights, and GenAI to drive measurable impact - replatforming systems in the cloud, optimizing customer journeys, or accelerating AI adoption across the enterprise. You’ll work at the intersection of strategy and execution, solving complex problems alongside smart, curious teammates across Canada and Poland. Backed by 20+ years of experience, a drive for excellence, and a culture rooted in growth and collaboration, this is where you thrive if you’re looking to deliver meaningful, high-stakes software solutions.
We’re Building a More Inclusive Tech Industry
We believe diversity leads to better outcomes. Nearly half of our team was born outside of Canada, and we speak 19+ languages. We’re 31% women, 57% BIPOC, and 14% LGBTQIA+. We’ve doubled the number of women in tech roles in the past year, and maintain a 0% gender pay gap across our delivery and technology teams. Inclusion here isn’t a buzzword, it’s backed by data, policy, and accountability.
How We Work Together
We’re a close-knit, collaborative group who care about doing excellent work, and doing it with integrity. Our values shape how we show up every day:
Think Big – Dream it, plan it, ship it
Be Open & Collaborate – Diverse minds build better solutions
Never Fail a Client – Own the outcome
Grow Our People – Feedback, learning, leadership
Do the Right Thing – Even when it’s hard
Embrace Change – Adapt fast, stay curious
Our people say it best: “Employees of different backgrounds interact well within our company” - and 97% agree. Another 96% say “Architech respects individuals and values their differences.”

Data Architect (Microsoft Azure / Microsoft Fabric / AWS/ Databricks)

Role Overview

The Data Architect (Azure Data Architect or Data Platform Architect) designs and leads the build-out of scalable, AI-ready data solutions using Microsoft Fabric, Azure, or AWS with Databricks data ecosystem. This role connects business goals to data architecture, ensuring platforms are secure, performant, and optimized for analytics and AI use cases.

You will define how data flows from raw ingestion (bronze) through transformation (silver) to curated, analytics-ready models (gold). You will collaborate with engineering and business peers to design data environments that enable analytics, automation, and AI-driven insight.

Key Responsibilities

  • Architect Microsoft Fabric environments: Design end-to-end data architectures, defining ingestion, transformation, and curation patterns that support analytics and AI workloads.
  • Lead Design and implement scalable data architectures on Databricks, including lakehouse solutions leveraging Delta Lake, Unity Catalog, and medallion architecture (bronze/silver/gold layers) to support enterprise analytics and ML workloads.
  • Lead Design and manage data lake architectures - Ensure efficient replication, synchronization, and data flow across Fabric workspaces and multi-zone environments.
  • Define business-aligned data models - Partner with stakeholders to understand reporting, analytics, and AI needs and design scalable, flexible data models.
  • Define data governance, security, and access control strategies — Use Unity Catalog and Microsoft Purview for centralized metadata management, fine-grained permissions, RBAC, encryption (at rest/in transit), data masking, and lineage tracking across workspaces.
  • AI readiness - Define structures, metadata, and access patterns that make data discoverable and usable for AI workloads such as retrieval-augmented generation (RAG), intelligent search, and summarization.
  • Familarity in implementing and managing Databricks Genie to enable self-service, natural language querying of enterprise data, empowering business users with AI-driven insights.
  • Framework alignment - Ensure all data architectures align with Microsoft's Cloud Adoption Framework (CAF) and the Azure/AWS Well-Architected Framework for consistency, scalability, and governance.
  • Performance and cost optimization - Guide architecture decisions related to Fabric SKUs, OneLake storage, and data refresh strategies for efficient scale and cost.
  • Collaboration and mentorship - Work closely with Data Engineers to translate architecture into delivery, promote data quality, and ensure design consistency.
  • Documentation and enablement - Produce reference architectures, blueprints, and reusable standards that accelerate future projects and maintain governance consistency.

Skills and Qualifications

  • 7+ years of experience in data architecture, data engineering, or data platform design, including:

At least 2 years working within the Microsoft Azure data ecosystem (Fabric, Synapse, ADF, Power BI).

At least 2 years of hands-on experience with Databricks (Delta Lake, Unity Catalog, lakehouse architecture).

  • Strong grasp of data lakehouse design principles, including ELT/ETL patterns, medallion architecture (bronze/silver/gold), and schema evolution.
  • Proficiency in SQL, with working knowledge of Python for automation, validation, and pipeline scripting.
  • Hands-on experience with data governance and metadata management tools, such as Microsoft Purview and/or Databricks Unity Catalog.
  • Practical understanding of data security fundamentals — RBAC, encryption (at rest/in transit), data masking, and privacy best practices.
  • Strong communication and cross-functional collaboration skills, with the ability to translate business needs into technical architecture and work across engineering, analytics, and business teams.
  • Strategic, iterative mindset — comfortable operating in AI-ready, fast-evolving, client-facing environments.

Tools and Technologies

Microsoft Fabric, Azure Data Factory, Synapse, Power BI, Azure SQL, Databricks, Data Lake Storage, Vector DB, Microsoft Purview, Python, SQL, Git, Terraform or Bicep, Azure Monitor.

Nice to Have

  • Experience applying architecture frameworks — Microsoft's Cloud Adoption Framework (CAF) and/or the Azure/AWS Well-Architected Framework to ensure scalability and governance consistency
  • Exposure to AI/semantic data enablement — metadata enrichment, retrieval-augmented generation (RAG), knowledge graph design, vector databases, and embedding pipelines.
  • Familiarity with modern data architecture paradigms — data product thinking, domain-driven design, or data mesh principles.
  • Familiarity with vector databases, semantic search, and embedding pipelines.
  • Familiarity with our data sources — exposure to platforms such as ChurnZero, Zendesk, Salesforce, Gong, and RocketLane is a plus.

Architech is an equal opportunity employer committed to diversity. Should you require any accommodations prior to or during the interview process, please indicate this during the interview process. We strongly encourage applications from racialized people, people with disabilities, people from gender and sexually diverse communities and/or people with intersectional identities.